Applications

Key Points Product: Pure Inertial Navigation System (INS) Based on IMU Key Features: Components: Uses MEMS accelerometers and gyroscopes for real-time measurement of acceleration and angular velocity. Function: Integrates initial position and attitude data with IMU measurements to calculate real-time position and attitude. Applications: Ideal for indoor navigation, aerospace, autonomous systems, and robotics. Challenges: Addresses sensor errors, cumulative drift, and dynamic environment impacts with calibration and filtering methods. Conclusion: Provides precise positioning in challenging environments, with robust performance when combined with auxiliary positioning systems like GPS.   The law of instrument constant drift with temperature of a gyro theodolite is a complex phenomenon, which involves the interaction of multiple components and systems within the instrument. Instrument constant refers to the measurement reference value of the gyro-theodolite under specific conditions. It is crucial to ensure measurement accuracy and stability. Temperature changes will cause the drift of instrument constants, mainly because the differences in thermal expansion coefficients of materials cause changes in the instrument structure, and the performance of electronic components changes with temperature changes. This drift pattern is often nonlinear because different materials and components respond differently to temperature. In order to study the drift of the instrument constants of a gyro theodolite with temperature, a series of experiments and data analysis are usually required. This includes calibrating and measuring the instrument at different temperatures, recording changes in instrument constants, and analyzing the relationship between temperature and instrument constants. Through the analysis of experimental data, the trend of instrument constants changing with temperature can be found, and an attempt can be made to establish a mathematical model to describe this relationship. Such models can be based on linear regression, polynomial fitting, or other statistical methods and are used to predict and compensate for drift in instrument constants at different temperatures. Understanding the drift of the instrument constants of a gyro theodolite with temperature is very important to improve measurement accuracy and stability. By taking corresponding compensation measures, such as temperature control, calibration and data processing, the impact of temperature on instrument constants can be reduced, thereby improving the measurement performance of the gyro theodolite. It should be noted that the specific drift rules and compensation methods may vary depending on different gyro theodolite models and application scenarios. Therefore, in practical applications, corresponding measures need to be studied and implemented according to specific situations. The study of the drift pattern of instrument constants of gyro theodolite with temperature usually involves monitoring and analyzing the performance of the instrument under different temperature conditions. The purpose of such research is to understand how changes in temperature affect the instrument constants of a gyro theodolite and possibly find a way to compensate or correct for this temperature effect. Instrumental constants generally refer to the inherent properties of an instrument under specific conditions, such as standard temperature. For gyro theodolite, instrument constants may be related to its measurement accuracy, stability, etc. When the ambient temperature changes, the material properties, mechanical structure, etc. inside the instrument may change, thus affecting the instrument constants. To study this drift pattern, the following steps are usually required: Select a range of different temperature points to cover the operating environments a gyroscopic theodolite may encounter.Take multiple directional measurements at each temperature point to obtain sufficient data samples.Analyze the data and observe the trend of instrument constants as a function of temperature.Try to build a mathematical model to describe this relationship, such as linear regression, polynomial fitting, etc.Use this model to predict instrument constants at different temperatures and possibly develop methods to compensate for temperature effects. A mathematical model might look like this: K(T) = a + b × T + c × T^2 + … Among them, K(T) is the instrument constant at temperature T, and a, b, c, etc. are the coefficients to be fitted. This kind of research is of great significance for improving the performance of gyro theodolite under different environmental conditions. It should be noted that specific research methods and mathematical models may vary depending on specific instrument models and application scenarios. Summarize The law of instrument constant drift with temperature of a gyro theodolite is a complex phenomenon, which involves the interaction of multiple components and systems within the instrument. Instrument constant refers to the measurement reference value of the gyro-theodolite under specific conditions. It is crucial to ensure measurement accuracy and stability. Temperature changes will cause the drift of instrument constants, mainly because the differences in thermal expansion coefficients of materials cause changes in the instrument structure, and the performance of electronic components changes with temperature changes. This drift pattern is often nonlinear because different materials and components respond differently to temperature. In order to study the drift of the instrument constants of a gyro theodolite with temperature, a series of experiments and data analysis are usually required. This includes calibrating and measuring the instrument at different temperatures, recording changes in instrument constants, and analyzing the relationship between temperature and instrument constants. Through the analysis of experimental data, the trend of instrument constants changing with temperature can be found, and an attempt can be made to establish a mathematical model to describe this relationship. Such models can be based on linear regression, polynomial fitting, or other statistical methods and are used to predict and compensate for drift in instrument constants at different temperatures. Understanding the drift of the instrument constants of a gyro theodolite with temperature is very important to improve measurement accuracy and stability. By taking corresponding compensation measures, such as temperature control, calibration and data processing, the impact of temperature on instrument constants can be reduced, thereby improving the measurement performance of the gyro theodolite. It should be noted that the specific drift rules and compensation methods may vary depending on different gyro theodolite models and application scenarios. Therefore, in practical applications, corresponding measures need to be studied and implemented according to specific situations. The study of the drift pattern of instrument constants of gyro theodolite with temperature usually involves monitoring and analyzing the performance of the instrument under different temperature conditions. The purpose of such research is to understand how changes in temperature affect the instrument constants of a gyro theodolite and possibly find a way to compensate or correct for this temperature effect. Instrumental constants generally refer to the inherent properties of an instrument under specific conditions, such as standard temperature. For gyro theodolite, instrument constants may be related to its measurement accuracy, stability, etc. When the ambient temperature changes, the material properties, mechanical structure, etc. inside the instrument may change, thus affecting the instrument constants. To study this drift pattern, the following steps are usually required: Select a range of different temperature points to cover the operating environments a gyroscopic theodolite may encounter.Take multiple directional measurements at each temperature point to obtain sufficient data samples.Analyze the data and observe the trend of instrument constants as a function of temperature.Try to build a mathematical model to describe this relationship, such as linear regression, polynomial fitting, etc.Use this model to predict instrument constants at different temperatures and possibly develop methods to compensate for temperature effects. A mathematical model might look like this: K(T) = a + b × T + c × T^2 + … Among them, K(T) is the instrument constant at temperature T, and a, b, c, etc. are the coefficients to be fitted. This kind of research is of great significance for improving the performance of gyro theodolite under different environmental conditions. It should be noted that specific research methods and mathematical models may vary depending on specific instrument models and application scenarios.   MG502 MEMS Gyroscope MG502    

Key Points Product: MEMS Gyroscope Borehole North Finding System Key Features: Components: Employs MEMS gyroscopes for north-seeking, featuring compact size, low cost, and high shock resistance. Function: Uses an improved two-position method (90° and 270°) and real-time attitude correction for precise north determination. Applications: Optimized for downhole drilling systems in complex underground environments. Data Fusion: Combines gyroscope data with local magnetic declination corrections for true north calculation, ensuring accurate navigation during drilling. Conclusion: Delivers precise, reliable, and independent north-finding capabilities, ideal for borehole and similar applications. The new MEMS gyroscope is a kind of inertial gyro with simple structure, which has the advantages of low cost, small size and resistance to high shock vibration. The inertial north seeking gyroscope can complete the independent north seeking all weather without external restrictions, and can achieve fast, high efficiency, high precision and continuous work. Based on the advantages of MEMS gyro, MEMS gyro is very suitable for downhole north finding system. This paper describes the segmented fusion research of MEMS gyro borehole north finding system. The following will introduce the improved two-position north finding, the scheme of MEMS gyro borehole fusion north finding and the determination of north finding value. Improved two-position north finding The static two-position north seeking scheme generally selects 0° and 180° as the initial and end positions of north seeking. After repeated experiments, the gyro output angular velocity is collected, and the final north seeking Angle is obtained by combining the local latitude. The experiment adopted the two-position method every 10°, collected 360° of the turntable, and a total of 36 sets of data were collected. After averaging each set of data, the measured solution values were shown in Figure 1 below. Figure 1 Fitting curve of gyroscope output from 0 to 360° As can be seen from Figure 1, the output fitting curve is a cosine curve, but the experimental data and angles are still small, and the experimental results lack accuracy. Repeated experiments were conducted, and the Angle of acquisition was extended to 0~660°, and the two-position method was conducted every 10° from 0°, and the data results were shown in Figure 2. The trend of the image is cosine curve, and there are obvious differences in data distribution. At the crest and trough of the cosine curve, the distribution of data points is scattered and the degree of fit to the curve is low, while at the place with the highest slope of the curve, the fit of data points to the curve is more obvious. Figure 2 Fitting curve of gyroscope output at two positions 0~660° Combined with the relationship between azimuth and gyro output amplitude in Figure 3, it can be concluded that the data fit is better when the two-position north finding is adopted at 90° and 270°, indicating that it is easier and more accurate to detect the north Angle in the east-west direction. Therefore, 90°, 270°, instead of 0° and 180°, are used in this paper as the two-position north seeking gyro output acquisition positions. Figure 3 Relation between azimuth and gyro output amplitude MEMS gyroscope borehole fusion northfinding When MEMS gyro is used in borehole north finding system, it is faced with complex environment, and there will be variable attitude Angle with drill bit drilling, so the solution of north Angle becomes much more complicated. In this section, based on the improvement of the two-position north finding scheme in the previous section, a method is proposed to obtain the attitude Angle by controlling rotation according to the output data information, and the included Angle with the north is obtained. The specific flow chart is shown in Figure 4. The MEMS gyroscope is transmitted to the upper computer through RS232 data interface. As shown in Figure 4, after the initial north Angle is obtained by searching north at the two positions, the next step of drilling while drilling is carried out. After receiving the north seeking instruction, the drilling work stops. The attitude Angle output by MEMS gyro is collected and transmitted to the upper computer. The rotation of the borehole north seeking system is controlled by the attitude Angle information, and the roll Angle and pitch Angle are adjusted to 0. The heading Angle at this moment is the Angle between the sensitive axis and the magnetic north direction. In this scheme, the Angle between MEMS gyroscope and true north direction can be obtained in real time by collecting attitude Angle information. Figure 4 Fusion north finding flow chart The north seeking value is determined In the fusion north finding scheme, the improved two-position north finding was performed on the MEMS gyroscope. After the north finding was completed, the initial north position was obtained, the heading Angle θ was recorded, and the initial attitude state was (0,0,θ), as shown in Figure 5(a). When the bit is drilling, the attitude Angle of the gyroscope changes, and the roll Angle and pitch Angle are regulated by the rotary table, as shown in Figure 5(b). As shown in Figure 5(b), when drilling the bit, the system receives the attitude Angle information of the attitude instrument, and needs to judge the sizes of roll Angle γ ‘and pitch Angle β’, and rotate them through the rotation control system to make them turn to 0. At this time, the output heading Angle data is the Angle between the sensitive axis and the magnetic north direction. The Angle between the sensitive axis and the true north direction should be obtained according to the relationship between the magnetic north and the true north direction, and the true north Angle should be obtained by combining the local magnetic declination Angle. The solution is as follows: θ’=Φ-∆φ In the above formula, θ ‘drill bit and the true north direction Angle, ∆φ is the local magnetic declination Angle, Φ is the drill bit and magnetic north Angle. Figure 5 Change of initial and drilling attitude Angle The north seeking value is determined In this chapter, the north finding scheme of MEMS gyroscope underground north finding system is studied. Based on the two-position north finding scheme, an improved two-position north finding scheme with 90° and 270° as starting positions is proposed. With the continuous progress of MEMS gyroscope, MEMS north-seeking gyroscope can achieve independent north finding, such as MG2-101, its dynamic measurement range is 100°/s, can work in the environment of -40 ° C ~+85 ° C, its bias instability is 0.1°/hr, and the angular velocity random walk is 0.005°/√hr. I hope you can understand the north finding scheme of MEMS gyroscope through this article, and look forward to discussing professional issues with you.   MG502 MEMS Gyroscope MG502    

Key Points Product: Integrated Optical Chip-Based Fiber Optic Gyroscope Key Features: Components: Uses an integrated optical chip combining functions like luminescence, beam splitting, modulation, and detection on a lithium niobate thin film (LNOI) platform. Function: Achieves “multi-in-one” integration of non-sensitive optical path functions, reducing size and production costs while enhancing polarization and phase modulation for accurate gyroscope performance. Applications: Suited for positioning, navigation, attitude control, and oil well inclination measurement. Optimization: Further improvements in polarization extinction ratio, emission power, and coupling efficiency can enhance stability and accuracy. Conclusion: This integrated design paves the way for miniaturized, low-cost fiber optic gyroscopes, meeting the growing demand for compact and reliable inertial navigation solutions. With the advantages of all-solid state, high performance and flexible design, fiber optic gyroscope has become the mainstream inertial gyroscope, which is widely used in many fields such as positioning and navigation, attitude control and oil well inclination measurement. Under the new situation, the new generation of inertial navigation system is developing towards miniaturization and low cost, which puts forward higher and higher requirements for the comprehensive performance of gyroscope such as volume, accuracy and cost. In recent years, hemispherical resonator gyro and MEMS gyro have developed rapidly with the advantage of small size, which has a certain impact on the fiber optic gyro market. The main challenge of traditional optical gyro volume reduction is the reduction of optical path volume. In the traditional scheme, the optical route of fiber optic gyro is composed of several discrete optical devices, each of which is realized based on different principles and processes and has independent packaging and pigtail. As a result, the device volume under the prior art is close to the reduction limit, and it is difficult to support the further reduction of the volume of fiber optic gyro. Therefore, it is urgent to explore new technical solutions to realize the effective integration of different functions of the optical path, greatly reduce the volume of the gyro optical path, improve the process compatibility, and reduce the production cost of the device. With the development of semiconductor integrated circuit technology, integrated optical technology has gradually achieved breakthroughs, and the feature size has been continuously reduced, and it has entered the micro and nano level, which has greatly promoted the technical development of integrated optical chips, and has been applied in optical communication, optical computing, optical sensing and other fields. The integrated optical technology provides a new and promising technical solution for the miniaturization and low cost of fiber optic gyro optical path. 1 Integrated optical chip scheme design 1.1 Overall Design The traditional optical routing light source (SLD or ASE), fiber taper coupler (referred to as “coupler”), Y branch waveguide phase modulator (referred to as “Y waveguide modulator”), detector, sensitive ring (fiber ring). Among them, the sensitive ring is the core unit of the sensitive Angle rate, and its volume size directly affects the precision of the gyro.We propose a hybrid integrated chip, which consists of a light source component, a multifunctional component and a detection component through hybrid integration. Among them, the light source part is an independent component, which is composed of SLD chip, isolation collimation component and peripheral components such as heat sink and semiconductor cooler. The detection module consists of a detection chip and a transresistance amplifier chip. The multifunctional module is the main body of hybrid integrated chip, which is realized based on lithium niobate thin film (LNOI) chip, and mainly includes optical waveguide, mode-spot conversion, polarizer, beam splitter, mode attenuator, modulator and other on-chip structures. The beam emitted by the SLD chip is transmitted into the LNOI waveguide after isolation and collimation.The polarizer deflects the input light, and the mode attenuator attenuates the non-working mode. After the beam splitter splits the beam and modulator modulates the phase, the output chip enters the sensitive ring and the sensitive angular rate. The light intensity is captured by the detector chip, and the generated photoelectric output flows through the transresistance amplifier chip to the demodulation circuit.The hybrid integrated optical chip has the functions of luminescence, beam splitting, beam combining, deflection, modulation, detection, etc. It realizes the “multi-in-one” integration of non-sensitive functions of gyro optical path. Fiber optic gyroscopes depend on the sensitive Angle rate of coherent beam with high degree of polarization, and the polarization performance directly affects the precision of gyroscopes. The traditional Y-waveguide modulator itself is an integrated device, which has the functions of deflection, beam splitting, beam combining and modulation. Thanks to material modification methods such as proton exchange or titanium diffusion, Y-waveguide modulators have extremely high deflection ability. However, thin film materials need to take into account the requirements of size, integration and deflection ability, which can not be met by material modification methods. On the other hand, the mode field of thin film optical waveguide is much smaller than that of bulk material optical waveguide, resulting in changes in electrostatic field distribution and electrorefractive index parameters, and the electrode structure needs to be redesigned. Therefore, the polarizer and modulator are the core design points of the “all-in-one” chip. 1.2 Specific Design The polarization characteristics are obtained by structural bias, and an on-chip polarizer is designed, which consists of curved waveguide and straight waveguideAgreed. The curved waveguide can limit the difference between the transmission mode and the non-transmission mode, and achieve the effect of mode bias. The transmission loss of the transmission mode is reduced by setting the offset.The transmission characteristics of optical waveguide are mainly affected by scattering loss, mode leakage, radiation loss and mode mismatch loss. Theoretically, the scattering loss and mode leakage of small curved waveguides are small, which are mainly limited by the late process. However, the radiation loss of curved waveguides is inherent and has different effects on different modes. The transmission characteristics of the curved waveguide are mainly affected by the mode mismatch loss, and there is mode overlap at the junction of the straight waveguide and the curved waveguide, resulting in a sharp increase in mode scattering. When the light wave is transmitted into the polarized waveguide, due to the existence of curvature, the effective refractive index of the light wave mode is different in the vertical direction and the parallel direction, and the mode restriction is different, which results in different attenuation effects for TE and TM modes.Therefore, it is necessary to design the bending waveguide parameters to achieve the deflection performance. Among them, bending radius is the key parameter of bending waveguide. The transmission loss under different bending radius and the loss comparison between different modes are calculated by FDTD eigenmode solver. The calculated results show that the loss of the waveguide decreases with the increase of the radius at small bending radius. On this basis, the relationship between polarization property (ratio of TE mode to TM mode) and bending radius is calculated, and the polarization property is inversely proportional to bending radius. The determination of the bending radius of the on-chip polarizer should consider the theoretical calculation, the simulation results, the technological capability and the actual demand.The finite difference Time domain (FDTD) is used to simulate the transmitted light field of the on-chip polarizer. The TE mode can pass through the waveguide structure with low loss, while the TM mode can produce obvious mode attenuation, so as to obtain polarized light with high extinction ratio. By increasing the number of cascaded waveguides, the extinction ratio of the polarization-extinction ratio can be further improved, and better than -35dB polarization extinction ratio performance can be obtained on the micron scale. At the same time, the structure of the waveguide on chip is simple, and it is easy to realize the low-cost fabrication of the device. 2 Integrated optical chip performance verification The LNOI main chip of the integrated optical chip is an unsliced sample engraved with multiple chip structures, and the size of a single LNOI main chip is 11mm×3mm. The performance test of integrated optical chip mainly includes the measurement of spectral ratio, polarization extinction ratio and half-wave voltage.Based on the integrated optical chip, a gyroscope prototype is built, and the performance test of the integrated optical chip is carried out. Static zero bias performance of a gyro prototype based on integrated optical chip in a non-vibration isolated foundation at room temperature. set-basedThe gyroscope formed into optical chip has a long time drift in the start-up segment, which is mainly caused by the start-up characteristic of light source and the large loss of optical link. In the 90min test, the zero bias stability of the gyroscope is 0.17°/h (10s). Compared with the gyroscope based on traditional discrete devices, the zero bias stability index deteriorates by an order of magnitude, indicating that the integrated optical chip needs to be further optimized. Main optimization directions: improve the polarization extinction ratio of the chip, improve the luminous power of the light-emitting chip, improve the end-coupling efficiency of the chip, and reduce the overall loss of the integrated chip. 3 Summary We propose an integrated optical chip based on LNOI, which can realize the integration of non-sensitive functions such as luminescence, beam splitting, beam combining, deflection, modulation and detection. The zero bias stability of the gyro prototype based on the integrated optical chip is 0.17°/h. Compared with the traditional discrete devices, the performance of the chip still has a certain gap, which needs to be further optimized and improved. We preliminarily explore the feasibility of fully integrated optical path functions except ring, which can maximize the application value of integrated optical chip in gyro, and meet the development needs of miniaturization and low cost of fiber optic gyro. GF50 Single-Axis Medium Accuracy Military Standard Fiber Optic Gyroscope   GF60 Single Axis Fiber Gyro Low Power Fiber Optic Gyro Imu Angular Rate for Navigation  

Key Points Product: Pure Inertial Navigation System (INS) Based on IMU Key Features: Components: Uses MEMS accelerometers and gyroscopes for real-time measurement of acceleration and angular velocity. Function: Integrates initial position and attitude data with IMU measurements to calculate real-time position and attitude. Applications: Ideal for indoor navigation, aerospace, autonomous systems, and robotics. Challenges: Addresses sensor errors, cumulative drift, and dynamic environment impacts with calibration and filtering methods. Conclusion: Provides precise positioning in challenging environments, with robust performance when combined with auxiliary positioning systems like GPS.   Pure inertial data (IMU) position calculation is a common positioning technology. It calculates the target object in real time by using the acceleration and angular velocity information obtained by the Inertial Measurement Unit (IMU), combined with the initial position and attitude information. s position. This article will introduce the principles, application scenarios and some related technical challenges of pure inertial navigation data position calculation. 1. Principle of position calculation based on pure inertial navigation data Pure inertial navigation data position calculation is a positioning method based on the principle of inertial measurement. IMU is a sensor that integrates an accelerometer and a gyroscope. By measuring the acceleration and angular velocity of the target object in three directions, the position and attitude information of the target object can be derived. In pure inertial navigation data position calculation, it is first necessary to obtain the initial position and attitude information of the target object. This can be achieved by introducing other sensors (such as GPS, compass, etc.) or manual calibration. The initial position and attitude information play an important role in the solution process. They provide a starting point so that the acceleration and angular velocity data measured by the IMU can be converted into the actual displacement and attitude changes of the target object. Then, based on the acceleration and angular velocity data measured by the IMU, combined with the initial position and attitude information, numerical integration or filtering algorithms can be used to calculate the position of the target object in real time. The numerical integration method obtains the speed and displacement of the target object by discretizing and integrating the acceleration and angular velocity data. The filtering algorithm uses methods such as Kalman filtering or extended Kalman filtering to filter the data measured by the IMU to obtain the position and attitude estimation of the target object. 2. Application scenarios of pure inertial navigation data position calculation Position calculation based on pure inertial navigation data is widely used in many fields. Among them, indoor navigation is one of the typical application scenarios for pure inertial navigation data position calculation. In indoor environments, GPS signals are usually unable to reach, and pure inertial navigation data position calculation can use the data measured by IMU to achieve accurate positioning of target objects indoors. This is of great significance in fields such as autonomous driving and indoor navigation robots. Pure inertial navigation data position calculation can also be used in the aerospace field. In aircraft, since the GPS signal may be interfered at high altitudes or far from the ground, pure inertial navigation data position calculation can be used as a backup positioning method. It can calculate the position and attitude of the aircraft in real time through the data measured by the IMU, and provide it to the flight control system for attitude stabilization and flight path planning. 3. Challenges of position calculation using pure inertial navigation data Position calculation based on pure inertial navigation data still faces some challenges in practical applications. First of all, the IMU sensor itself has errors and noise, which will affect positioning accuracy. In order to improve the solution accuracy, the IMU sensor needs to be calibrated and error compensated, and an appropriate filtering algorithm is used to reduce the error. Position calculation based on pure inertial navigation data is prone to cumulative errors during long-term movements. Due to the characteristics of the integration operation, even if the measurement accuracy of the IMU sensor is high, long-term integration will lead to the accumulation of positioning errors. In order to solve this problem, other positioning means (such as GPS, visual sensors, etc.) can be introduced for auxiliary positioning, or a tightly coupled inertial navigation method can be used. Position calculation based on pure inertial navigation data also needs to consider the impact of the dynamic environment. In a dynamic environment, the target object may be affected by external forces, causing deviations in the data measured by the IMU. In order to improve the robustness of the solution, the effects of dynamic environments can be compensated through methods such as motion estimation and dynamic calibration. Summarize Pure inertial data position calculation is a positioning method based on IMU measurement. By acquiring acceleration and angular velocity data, combined with initial position and attitude information, the position and attitude of the target object are calculated in real time. It has wide applications in indoor navigation, aerospace and other fields. However, pure inertial navigation data position calculation also faces challenges such as calibration error, cumulative error and dynamic environment. In order to improve the solution accuracy and robustness, appropriate calibration methods, filtering algorithms and auxiliary positioning methods need to be adopted. The MEMS IMU independently developed by Micro-Magic Inc has relatively high accuracy, such as UF300A and UF300B, which have higher accuracy and are navigation-grade products. If you want to know more about IMU, please contact our professional technicians as soon as possible.   UF300 High-precision Miniaturized Inertial Measurement Unit Fiber Optic Inertial Measurement Unit   -

Key Points Product: Fiber Optic Gyroscope-Based Deformation Detection System Key Features: Components: Incorporates high-precision fiber optic gyroscopes for angular velocity measurement and trajectory calculation. Function: Combines gyroscopic data with distance measurements to detect structural deformations with high accuracy. Applications: Suitable for civil engineering, structural health monitoring, and deformation analysis in bridges, buildings, and other infrastructures. Performance: Achieves deformation detection accuracy better than 10 μm at a running speed of 2 m/s using medium-precision gyroscopes. Advantages: Compact design, lightweight, low power consumption, and user-friendly operation for ease of deployment. Conclusion:This system provides precise and reliable deformation measurements, offering valuable solutions for engineering and structural analysis needs. 1 Method of engineering structure deformation detection based on fiber optic gyroscope The principle of the engineering structure deformation detection method based on fiber optic gyro is to fix the fiber optic gyro to the detection device, measure the angular velocity of the detection system when running on the measured surface of the engineering structure, measure the operating distance of the detection device, and calculate the operating trajectory of the detection device to realize the detection of engineering structure deformation. This method is referred to as the trajectory method in this paper. This method can be described as “two-dimensional plane navigation”, that is, the position of the carrier is solved in the plumb surface of the measured structure surface, and the trajectory of the carrier along the measured structure surface is finally obtained. According to the principle of trajectory method, its main error sources include reference error, distance measurement error and Angle measurement error. The reference error refers to the measurement error of the initial inclination Angle θ0, the distance measurement error refers to the measurement error of ΔLi, and the Angle measurement error refers to the measurement error of Δθi, which is mainly caused by the measurement error of the angular velocity of the fiber optic gyroscope. This paper does not consider the influence of reference error and distance measurement error on the deformation detection error, only the deformation detection error caused by the fiber optic gyroscope error is analyzed. 2 Analysis of deformation detection accuracy based on fiber optic gyroscope 2.1 Error modeling of fiber optic gyroscope in deformation detection applications Fiber optic gyro is a sensor for measuring angular velocity based on Sagnac effect. After the light emitted by the light source passes through the Y-waveguide, two beams of light rotating in opposite directions in the fiber ring are formed. When the carrier rotates relative to the inertial space, there is an optical path difference between the two beams of light, and the optical interference signal related to the rotational angular speed can be detected at the detector end, so as to measure the diagonal speed.The mathematical expression of the fiber optic gyro output signal is: F=Kw+B0+V. Where F is the gyro output, K is the scale factor, and ω is the gyroThe angular velocity input on the sensitive axis, B0 is the gyroscopic zero bias, υ is the integrated error term, including white noise and slowly varying components caused by various noises with long correlation time, υ can also be regarded as the error of zero bias.The sources of measurement error of fiber optic gyroscope include scale factor error and zero deviation error. At present, the scale factor error of the fiber optic gyroscope applied in engineering is 10-5~10-6. In the application of deformation detection, the angular velocity input is small, and the measurement error caused by the scale factor error is much smaller than that caused by the zero deviation error, which can be ignored. The DC component of the zero-bias error is characterized by the zero-bias repeatability Br, which is the standard deviation of the zero-bias value in multiple tests. The AC component is characterized by zero bias stability Bs, which is the standard deviation of the gyroscope output value from its mean in one test, and its value is related to the sampling time of the gyroscope. 2.2 Calculation of deformation error based on fiber optic gyroscope Taking the simple supported beam model as an example, the error of deformation detection is calculated, and the theoretical model of structural deformation is established. On this basis, the detection is setBased on the operating speed and sampling time of the system, the theoretical angular velocity of the fiber optic gyro can be obtained. Then the angular velocity measurement error of the fiber optic gyro can be simulated according to the zero deviation error model of the fiber optic gyro established above. 2.3 Example simulation calculation The simulation setting of running speed and sampling time adopts a range-varying mode, that is, the ΔLi passed by each sampling time is fixed, and the sampling time of the same line segment is changed by changing the running speed. For example, when the ΔLi is 1 mm, such as the running speed is 2 m/s, the sampling time is 0.5 ms. If the operating speed is 0.1 m/s, the sampling time is 10 ms. 3 Relationship between fiber optic gyroscope performance and deformation measurement error Firstly, the effect of zero-bias repeatability error is analyzed. When there is no zero bias stability error, the angular velocity measurement error caused by zero bias error is fixed, such as the faster the motion speed, the shorter the total measurement time, the smaller the impact of zero bias error, the smaller the deformation measurement error. When the running speed is fast, the zero bias stability error is the main factor causing the system measurement error. When the running speed is low, the zero bias repeatability error becomes the main source of the system measurement error.Using typical medium precision fiber optic gyro index, that is, zero bias stability is 0.5 °/h when sampling time is 1 s, Zero repeatability is 0.05 °/h. Compare the system measurement errors at the operating speed of 2 m/s, 1 m/s, 0.2 m/s, 0.1 m/s, 0.02 m/s, 0.01 m/s, 0.002 m/s and 0.001 m/s. When the operating speed is 2 m/s, The measurement error is 8.514μm (RMS), when the measurement speed is reduced to 0.2m /s, the measurement error is 34.089μm (RMS), when the measurement speed is reduced to 0.002m /s, the measurement error is 2246.222μm (RMS), as can be seen from the comparison results. The faster the running speed, the smaller the measuring error. Considering the convenience of engineering operation, the running speed of 2 m/s can achieve better than 10 μm measurement accuracy. 4 Summary Based on the simulation analysis of the engineering structure deformation measurement based on fiber optic gyro, the error model of fiber optic gyro is established, and the relationship between the deformation measurement error and the performance of fiber optic gyro is obtained by using the simple supported beam model as an example. The simulation results show that the faster the system runs, that is, the shorter the sampling time of the fiber optic gyroscope, the higher the deformation measurement accuracy of the system when the sampling number is unchanged and the distance detection accuracy is guaranteed. With the typical medium precision fiber optic gyro index and the running speed of 2 m/s, the deformation measurement accuracy of better than 10 μm can be achieved.Micro-Magic Inc GF-50 has a diameter of φ50*36.5mm and an accuracy of 0.1º/h. GF-60 precision 0.05º/h, belongs to the high tactical level of the fiber optic gyroscope, our company produced gyroscope with small size, light weight, low power consumption, fast start, simple operation, easy to use and other characteristics, widely used in INS, IMU, positioning system, north finding system, platform stability and other fields. If you are interested in our fiber optic gyro, please feel free to contact us. GF50 Single-Axis Medium Accuracy Military Standard Fiber Optic Gyroscope   GF60 Single Axis Fiber Gyro Low Power Fiber Optic Gyro Imu Angular Rate for Navigation  

Key Points Product: IMU for Pipeline Inspection Key Features: Components: Equipped with MEMS gyroscopes and accelerometers for measuring angular velocity and acceleration. Function: Monitors pipeline conditions by detecting bends, diameter variations, and cleanliness through precise measurements of motion and orientation. Applications: Used in pipeline inspection, including strain identification, diameter measurement, and cleaning processes. Data Processing: Collects and processes data for accurate assessment of pipeline health, curvature, and strain. Conclusion: Provides critical insights for pipeline maintenance, improving efficiency and reliability in inspection and maintenance operations. 1.IMU measurement principle IMU (Inertial Measurement Unit) is a device that can measure the angular velocity and acceleration of an object in three-dimensional space. Its core components usually include a three-axis gyroscope and a three-axis accelerometer. Gyroscopes are used to measure the angular velocity of an object about three orthogonal axes, while accelerometers are used to measure the acceleration of an object along three orthogonal axes. By integrating these measurements, the velocity, displacement and attitude information of the object can be obtained. 2.Pipe bending strain identification In pipeline inspection, IMU can be used to identify the bending strain of the pipeline. When an IMU is installed on a pig or other mobile device and moves within a pipeline, it can sense changes in acceleration and angular velocity caused by pipeline bending. By analyzing this data, the degree and location of pipe bends can be identified. 3.Diameter measurement and pipe cleaning process The diameter measuring and cleaning process is an important part of pipeline maintenance. In this process, a caliper pig equipped with an IMU is used to move along the pipeline, measure the inner diameter of the pipeline, and record the shape and size of the pipeline. This data can be used to assess the health of pipelines and predict possible maintenance needs. 4.Steel brush cleaning process The steel brush pigging process is used to remove dirt and sediment from the inner walls of pipelines. In this process, a pig with a steel brush and an IMU moves along the pipeline, cleaning the inner wall of the pipeline through brushing and scouring. The IMU can record the geometric information and cleanliness of the pipeline during this process. 5.IMU detection process The IMU inspection process is a key step in using IMU for data collection and measurement during pipeline maintenance. The IMU is installed on a pig or similar equipment and moves inside the pipeline while recording acceleration, angular velocity and other parameters. This data can be used to analyze the health of the pipeline, identify potential problems, and provide a basis for subsequent maintenance and management. 6.Data acquisition and post-processing After completing the IMU detection process, the collected data need to be collected and post-processed. Data acquisition involves transferring raw data from the IMU device to a computer or other data processing device. Post-processing involves cleaning, calibrating, analyzing and visualizing the data. Through post-processing, useful information can be extracted from the original data, such as the shape, size, bending degree, etc. of the pipe. 7.Speed and attitude measurement IMU can calculate the speed and attitude of an object by measuring acceleration and angular velocity. In pipeline inspection, measurement of speed and attitude is critical to assess the health of the pipeline and identify potential problems. By monitoring the speed and attitude changes of the pig in the pipeline, the shape, bending degree and possible obstacles of the pipeline can be inferred. 8.Pipe Curvature and Strain Assessment Using the data measured by the IMU, the curvature and strain of the pipeline can be evaluated. By analyzing acceleration and angular velocity data, the radius of curvature and bending angle of the pipe at different locations can be calculated. At the same time, combined with the material properties and loading conditions of the pipe, the strain level and stress distribution of the pipe at the bend can also be evaluated. This information is important for predicting the life of pipelines, assessing safety, and developing maintenance plans. Summarize To sum up, IMU plays an important role in pipeline inspection. By measuring parameters such as acceleration and angular velocity, comprehensive assessment and maintenance of pipeline health can be achieved. With the continuous advancement of technology and the expansion of application fields, the application of IMU in pipeline inspection will become more and more extensive. The MEMS IMU independently developed by Micro-Magic Inc has relatively high accuracy, such as U5000 and U7000, which are more accurate and are navigation-grade products. If you want to know more about IMU, please contact our professional technicians as soon as possible. U7000 Industrial Grade Temperature Compsensated Full Calibrated Strapdown 6Dof With Kalman Filter Algorithm   U5000 Rs232/485 Gyroscope Imu For Radar/infrared antenna stabilization platform  

Key Points Product: Inertial Navigation System (INS) and Global Positioning System (GPS) Key Features: Components: INS uses accelerometers and gyroscopes; GPS relies on satellite signals. Function: INS provides autonomous navigation without external signals; GPS offers precise geolocation with global coverage. Applications: INS is ideal for underwater, underground, and space; GPS is used in personal navigation, military, and tracking. Integration: Combining INS and GPS enhances accuracy and reliability in complex environments. Conclusion: Choosing between INS and GPS depends on specific needs, with many applications benefiting from their integration for optimal navigation solutions. For complex vehicles such as airplanes, autonomous vehicles, ships, spacecraft, submarines, and UAVs, having an accurate system to maintain and control perfect movement is essential. Two of the most prominent navigation systems in use today are the Inertial Navigation System (INS) and the Global Positioning System (GPS). Both have their unique advantages and applications, but choosing the best system for your needs depends on several factors. This article will explore the differences, strengths, and ideal use cases for each system to help you make an informed decision. Understanding INS and GPS Inertial Navigation System (INS): The MEMS north finder can provide heading information to the moving body in a fully autonomous manner, working without relying on satellites, not affected by climate, and not requiring complex operations. It not only provides the data output interface for the computer, but also provides a good man-machine interface. The MEMS North finder is mainly composed of the inertial measurement module (IMU) and the line part, and the hardware block diagram is shown in Figure 1. Inertial measurement unit (IMU) is composed of gyroscope and rotary mechanism. The circuit part is mainly composed of four circuit boards, including: power board, control board, power amplifier board and base plate. Table 1 shows the components of the north seeking system. Global Positioning System (GPS): The Global Positioning System is a satellite-based navigation system that provides geolocation and time information to a GPS receiver anywhere on or near the Earth where there is an unobstructed line of sight to four or more GPS satellites. GPS is highly accurate and provides continuous positioning information, making it ideal for a wide range of applications, from personal navigation to military operations. However, GPS signals can be obstructed by buildings, trees, or atmospheric conditions, leading to potential inaccuracies. GPS technology is primarily used for location data, mapping, tracking moving objects, navigation, and timing estimations and measurements. However, this information relies on satellite connections, and if the GPS device cannot connect to at least four satellites, the data provided will be insufficient for full operational functionality.   Strengths and Weaknesses INS Strengths: Independence: Does not rely on external signals, making it useful in GPS-denied environments. Instantaneous Response: Provides immediate updates on position and velocity. Robustness: Less susceptible to jamming or signal interference. INS Weaknesses: Drift: Accumulated errors can lead to inaccuracies over time. Complexity: Generally more complex and expensive than GPS systems. Fig.2 Pros And Cons Of Ins And Gnss GPS Strengths: Accuracy: Provides precise location information, often within a few meters. Coverage: Global coverage with continuous updates. Ease of Use: Widely available and relatively inexpensive. GPS Strengths: Signal Dependency: Requires a clear line of sight to satellites, which can be obstructed. Vulnerability: Susceptible to jamming, spoofing, and interference. Combining INS and GPS In many applications, INS and GPS are used together to leverage their complementary strengths. By integrating GPS data with INS, the system can correct for INS drift and provide more reliable and accurate navigation. This combination is particularly valuable in aviation, where continuous and precise navigation is critical, and in autonomous vehicles, where robust and accurate positioning is essential for safe operation. With the rapid development of micro-electromechanical systems (MEMS), smaller and more portable GPS-aided integrated navigation systems have been developed, such as Micro-Magic Inc‘s three models with different accuracy levels. Among them, the ultra-high precision I6600 surveying and tactical-grade system is equipped with a powerful IMU, capable of outputting highly accurate position, velocity, and attitude information. Conclusion Choosing between INS and GPS depends on your specific needs and the environment in which you will be operating. If you require a system that is independent of external signals and can function in challenging environments, INS may be the best choice. However, if you need highly accurate, continuous positioning information with global coverage, GPS is likely the better option. For many applications, combining both systems can provide the optimal solution, ensuring reliability and precision in navigation. By understanding the strengths and limitations of each system, you can make an informed decision and select the navigation system that best meets your requirements.   I6700 MEMS GNSS-Aided Inertial Navigation System    

Key Points Product: GNSS-aided MEMS Inertial Navigation System (INS) Key Features: Components: Equipped with MEMS gyroscopes and accelerometers for accurate inertial measurements, with GNSS support for enhanced navigation. Function: Combines short-term INS precision with long-term GNSS stability, delivering continuous navigation data. Applications: Suited for tactical operations, drones, robotics, and industrial automation. Data Fusion: Merges INS data with GNSS corrections to reduce drift and improve positioning accuracy. Conclusion: Delivers high precision and reliability, ideal for navigation tasks across diverse industries. In the noise reduction process of IMU (Inertial Measurement Unit), wavelet denoising is an effective method. The basic principle of wavelet denoising is to use the multi-resolution time-frequency localization characteristics of wavelets to decompose the components of different frequencies in the signal into different subspaces, and then process the wavelet coefficients in these subspaces to remove noise. Specifically, the process of wavelet denoising can be divided into the following three steps: 1.Perform wavelet transformation on the noisy IMU signal and decompose it into different wavelet subspaces. 2.Threshold the coefficients in these wavelet subspaces, that is, coefficients below a certain threshold are regarded as noise and set to zero, while coefficients above the threshold are retained, and these coefficients usually contain useful signal information. 3.Perform inverse transformation on the processed wavelet coefficients to obtain the denoised signal. This method can effectively remove the noise in the IMU signal and improve the quality and accuracy of the signal. At the same time, because the wavelet transform has good time-frequency characteristics, it can better retain the useful information in the signal and avoid excessive information loss during the denoising process. Please note that the specific threshold selection and processing methods may vary according to specific signal characteristics and noise conditions, and therefore need to be adjusted and optimized according to specific circumstances in actual applications. The IMU data denoising method based on wavelet decomposition is an effective signal processing technology used to remove noise from IMU (Inertial Measurement Unit) data. IMU data often contains high-frequency noise and low-frequency drift, which can affect the accuracy and performance of the IMU. The noise reduction method based on wavelet decomposition can effectively separate and remove these noises and drifts, thereby improving the accuracy and reliability of IMU data. Wavelet decomposition is a multi-scale analysis technique that can decompose signals into wavelet components of different frequencies and scales. By wavelet decomposing the IMU data, high-frequency noise and low-frequency drift can be separated and processed differently. The IMU data denoising method based on wavelet decomposition usually includes the following steps: 1.Perform wavelet decomposition on the IMU data and decompose it into wavelet components of different frequencies and scales. 2.According to the characteristics of the wavelet components, select an appropriate threshold or wavelet coefficient processing method to suppress or remove high-frequency noise. 3.Model and compensate for low-frequency drift to reduce its impact on IMU data. 4.Reconstruct the processed wavelet components to obtain denoised IMU data.   The IMU data denoising method based on wavelet decomposition has the following advantages: 1.Able to effectively separate and remove high-frequency noise and low-frequency drift, improving the accuracy and reliability of IMU data. 2.Have good time-frequency analysis capabilities and be able to process the time and frequency information of signals at the same time. 3.Suitable for different types of IMU data and different application scenarios, with strong versatility and flexibility. Summarize In short, the IMU data denoising method based on wavelet decomposition is an effective signal processing technology that can improve the accuracy and reliability of IMU data and provide more accurate and reliable data for inertial navigation, attitude estimation, motion tracking and other fields. support. The IMU independently developed by Micro-Magic Inc uses some relatively rigorous denoising methods to better demonstrate to consumers higher-precision and low-cost MEMS IMUs, such as U5000 and U3500 as navigation series MEMS IMUs. Technicians conducted various experiments to denoise the IMU data to better meet consumers’ accurate measurement of the motion state of objects. If you want to know more about IMU, please contact our relevant personnel. U3500 IMU MEMS Sensor IMU3500 CAN Output   U5000 Whatever you needs, CARESTONE is at your side.  

Key Points Product: Quartz Flexible Accelerometer Key Features: Components: Uses high-precision quartz flexible accelerometers for accurate acceleration and tilt measurements. Function: Vibration analysis helps identify sensor error coefficients, improving measurement accuracy and performance. Applications: Widely used in structural health monitoring, aerospace navigation, automotive testing, and industrial machinery diagnostics. Data Analysis: Combines vibration data with signal processing algorithms to optimize sensor models and enhance performance. Conclusion: Delivers precise and reliable acceleration measurements, with strong potential in various high-precision industries. 1.Introduction: In the realm of sensor technology, accelerometers play a pivotal role in various industries, from automotive to aerospace, healthcare to consumer electronics. Their ability to measure acceleration and tilt across multiple axes makes them indispensable for applications ranging from vibration monitoring to inertial navigation. Among the diverse types of accelerometers, quartz flexible accelerometers stand out for their precision and versatility. In this article, we delve into the intricacies of identifying quartz flexible accelerometers through vibration analysis, exploring their design, working principles, and the significance of vibration analysis in optimizing their performance. 2.Importance of Vibration Analysis: For the accelerometer to be identified, first, conduct multi-directional vibration table tests on it. Obtain rich raw data through data acquisition software. Then, based on the test data, on the one hand, combine the overall least squares algorithm to identify its high-order error coefficients, improve its signal model equation, enhance the measurement accuracy of the sensor, and explore the relationship between the high-order error coefficients of the accelerometer and its operating status. Seek methods to identify its operating status through the high-order error coefficients of the accelerometer. On the other hand, extract its effective feature set, train neural networks, and finally modularize the effective data analysis algorithm through virtual instrument technology. Develop application software for identifying the operating status of quartz flexible accelerometers to achieve rapid and accurate identification of sensor operating status. This will help personnel to promptly improve internal circuit structures, enhance the measurement accuracy of accelerometers, and improve the yield of manufactured products during the processing and manufacturing process. Vibration analysis serves as a cornerstone in the characterization and optimization of quartz flexible accelerometers. By subjecting these sensors to controlled vibrations across different frequencies and amplitudes, engineers can evaluate their dynamic response characteristics, including sensitivity, linearity, and frequency range. Vibration analysis helps identify potential sources of error or non-linearity in accelerometer output, enabling manufacturers to fine-tune sensor parameters for enhanced performance and accuracy. 3.Identification Process: The identification of quartz flexible accelerometers through vibration analysis involves a systematic approach encompassing experimental testing, data analysis, and validation. Engineers typically conduct vibration tests using calibrated shakers or vibration excitation systems, exposing the accelerometers to sinusoidal or random vibrations while recording their output signals. Advanced signal processing techniques such as Fourier analysis and spectral density estimation are employed to analyze the frequency response of the accelerometers and identify resonance frequencies, damping ratios, and other critical parameters. Through iterative testing and analysis, engineers refine the accelerometer model and validate its performance against specified criteria. 4.Applications and Future Prospects: Quartz flexible accelerometers find applications across a diverse array of industries, including structural health monitoring, aerospace navigation, automotive testing, and industrial machinery diagnostics. Their high precision, robustness, and versatility make them indispensable tools for engineers and researchers striving to understand and mitigate the effects of dynamic forces and vibrations. Looking ahead, ongoing advancements in sensor technology and signal processing algorithms are poised to further enhance the performance and capabilities of quartz flexible accelerometers, unlocking new frontiers in vibration analysis and dynamic motion sensing. In conclusion, the identification of quartz flexible accelerometers through vibration analysis represents a critical endeavor in sensor technology, enabling engineers to unlock the full potential of these precision instruments. By understanding the working principles, conducting thorough vibration analysis, and refining sensor performance, manufacturers and researchers can harness the capabilities of quartz accelerometers for a myriad of applications, ranging from structural monitoring to advanced navigation systems. As technological innovation continues to accelerate, the role of vibration analysis in optimizing sensor performance will remain paramount, driving advancements in precision measurement and dynamic motion sensing. 5.Conclusion Micro-Magic Inc provides high-precision quartz flexible accelerometers, such as AC1, with small error and high precision, which have a bias stability of 5μg, scale factor repeatability of 15~50 ppm, and a weight of 80g, and can be widely used in the fields of oil drilling, carrier microgravity measurement system, and inertial navigation.   AC1 Navigation Class Level Quartz Flexible Accelerometer With Measurement Range 50G Excellent Long-Term Stability And Repeatability    

Key Points Product: GNSS/MEMS INS Integrated Navigation System Key Features: Components: Combines MEMS inertial sensors with GNSS receivers for enhanced navigation capabilities. Function: Provides high-frequency updates and accurate position, speed, and attitude information by integrating inertial data with GNSS corrections. Applications: Ideal for drones, flight recorders, intelligent unmanned vehicles, and underwater vehicles. Data Fusion: Utilizes Kalman filtering to merge GNSS data with MEMS INS data, correcting accumulated errors and improving overall accuracy. Conclusion: This integrated system leverages the strengths of both technologies to enhance navigation performance and reliability, with wide-ranging applications across various industries. With the development of MEMS inertial devices, the accuracy of MEMS gyroscopes and MEMS accelerometers has gradually improved, leading to rapid advancements in the application of MEMS INS. However, the enhancement in the accuracy of MEMS inertial devices has not been sufficient to meet the increasingly high accuracy demands of MEMS INS. Thus, improving the accuracy of MEMS INS through error compensation algorithms and other methods has become a focus of MEMS INS research. To enhance the performance of MEMS INS, researchers have explored various methods to reduce the errors in these systems. There are four main approaches to reducing MEMS INS errors: Calibration and Compensation of Sensor Error Parameters: This involves using mathematical modeling and experimental tools to stimulate sensor errors, systematically calibrating deterministic errors at the system level, and then compensating for these errors through inertial navigation algorithms to improve overall performance.Rotation Modulation Technology: By applying appropriate rotation modulation schemes, sensor errors can be made to vary periodically without relying on external information sources. This automatic error compensation in the navigation algorithm suppresses the influence of sensor errors on MEMS INS.Inertial Device Redundancy Technology: Due to the low cost of MEMS inertial sensors, redundancy designs can be implemented. Redundancy in sensors can effectively reduce the impact of random errors on MEMS INS, thereby enhancing performance.Incorporating External Information Sources: Using Kalman filtering for integrated navigation to suppress the accumulation of MEMS INS errors. This article will further introduce the fourth method, which is the most practical and widely researched integrated navigation form— the GNSS/MEMS INS integrated navigation system. Reasons for Using GNSS to Assist MEMS INS MEMS INS is a type of dead reckoning system that measures the relative state from the previous to the current sampling moment. It does not rely on acoustic, optical, or electrical signals for measurement, making it highly resistant to external interference and deception. Its autonomy and reliability make it a core navigation system for various carriers such as aircraft, ships, and vehicles. Fig.1 lists the performance of INS of different grades. Fig.1 The Performance Of INS Of Different Grades. MEMS INS offers a high update rate and can output comprehensive state information, including position, speed, attitude, angular velocity, and acceleration, with high short-term navigation accuracy. However, MEMS INS requires additional information sources to initialize position, speed, and attitude, and its pure inertial navigation error accumulates over time, particularly in tactical and commercial-grade INS. The GNSS/MEMS INS combination can realize the complementary advantages of both systems: GNSS provides stable long-term accuracy and can offer initial values for position and speed, correcting the accumulated errors in MEMS INS through filtering. Meanwhile, MEMS INS can enhance the update rate of GNSS navigation output, enrich the types of state information output, and assist in detecting and eliminating GNSS observation faults. Basic Model of GNSS/MEMS INS Integrated Navigation The basic model of GNSS/MEMS INS integration reflects the functional relationship between the observed information from sensors (IMU and receivers) and the carrier navigation parameters (position, speed, and attitude), as well as the types and random models of sensor measurement errors. The carrier’s navigation parameters must be described in a specific reference coordinate system. Fig.2 Basic Model Of Gnssmems Ins Integrated Navigation Navigation problems typically involve two or more coordinate systems: the inertial sensors measure the carrier’s motion relative to inertial space, while the carrier’s navigation parameters (position and speed) are usually described in an Earth-fixed coordinate system for intuitive understanding. Commonly used coordinate systems in GNSS/INS integrated navigation include the Earth-centered inertial coordinate system, the Earth-centered Earth-fixed coordinate system, the local geographic coordinate system, and the body coordinate system. Currently, the algorithms for GNSS/MEMS INS integration in absolute navigation have matured, and many high-performance products have emerged on the market. For example, the three newly launched MEMS INS models by Micro-Magic Inc, shown in the image below, are suitable for applications in drones, flight recorders, intelligent unmanned vehicles, roadbed positioning and orientation, channel detection, unmanned surface vehicles, and underwater vehicles. Fig.3 The Three Newly Launched GNSS/MEMS INS By Micro-Magic Inc I3500 High Accuracy 3-Axis Mems Gyro I3500 Inertial Navigation System   I3700 High Accuracy Agricultural Gps Tracker Module Consumption Inertial Navigation System Mtk Rtk Gnss Rtk Antenna Rtk Algorithm  

Key Points Product: Fiber Optic Gyroscope (FOG) Key Features: Components: Based on optical fiber coils, utilizing the Sagnac effect for precise angular displacement measurements. Function: Offers high sensitivity and accuracy, ideal for determining orientation in moving objects. Applications: Widely used in military (e.g., missile guidance, tank navigation) and expanding into civilian sectors (e.g., automotive navigation, surveying). Data Fusion: Combines inertial measurements with advanced microelectronics for enhanced precision and stability. Conclusion: The fiber optic gyroscope is pivotal for high-precision navigation, with promising growth potential across diverse applications. Fiber optic gyroscope industry market With its unique advantages, fiber optic gyroscope has a broad development prospect in the field of precision physical quantity measurement. Therefore, exploring the influence of optical devices and physical environment on the performance of fiber optic gyros and suppressing the relative intensity noise have become the key technologies to realize the high precision fiber optic gyro. With the deepening of research, the integrated fiber gyroscope with high precision and miniaturization will be greatly developed and applied. Fiber optic gyroscope is one of the mainstream devices in the field of inertia technology at present. With the improvement of technical level, the application scale of fiber optic gyro will continue to expand. As the core component of fiber optic gyros, the market demand will also grow. At present, China’s high-end optical fiber ring still needs to be imported, and under the general trend of domestic substitution, the core competitiveness of China’s optical fiber ring enterprises and independent research and development capabilities still need to be further enhanced. At present, the optical fiber ring is mainly used in the military field, but with the expansion of the application of optical fiber gyroscope to the civilian field, the application proportion of optical fiber ring in the civilian field will be further improved. According to the "2022-2027 China Fiber Optic Gyroscope industry Market Survey and Investment Advice Analysis Report" : The fiber optic gyroscope is a sensitive element based on the optical fiber coil, and the light emitted by the laser diode propagates along the optical fiber in two directions. The difference of light propagation path determines the angular displacement of the sensitive element. Modern fiber optic gyro is an instrument that can accurately determine the orientation of moving objects. It is an inertial navigation instrument widely used in modern aviation, navigation, aerospace and national defense industries. Its development is of great strategic significance to a country’s industry, national defense and other high-tech development.Fiber optic gyro is a new all-solid-state fiber optic sensor based on Sagnac effect. Fiber optic gyro can be divided into interferometric fiber optic gyros (I-FOG), resonant fiber optic gyro (R-FOG) and stimulated Brillouin scattering fiber optic gyro (B-FOG) according to its working mode. According to its accuracy, fiber optic gyro can be divided into: low-end tactical level, high-end tactical level, navigation level and precision level. Fiber optic gyroscopes can be divided into military and civilian according to their openness. At present, most fiber optic gyros are used in military aspects: fighter and missile attitude, tank navigation, submarine heading measurement, infantry fighting vehicles and other fields. Civil use is mainly automobile and aircraft navigation, bridge surveying, oil drilling and other fields.Depending on the accuracy of the fiber optic gyroscope, its applications range from strategic weapons and equipment to commercial grade civilian fields. Medium and high-precision fiber optic gyroscopes are mainly used in high-end weapons and equipment fields such as aerospace, while low-cost, low-precision fiber optic gyroscopes are mainly used in oil exploration, agricultural aircraft attitude control, robots and many other civilian fields with low precision requirements. With the development of advanced microelectronics and optoelectronics technologies, such as photoelectric integration and the development of special fiber optics for fiber optic gyros, the miniaturization and low-cost of fiber optic gyros have been accelerated. Summary Micro-Magic Inc’s fiber optic gyro is mainly a medium precision tactical fiber optic gyro, compared with other manufacturers, low cost, long service life, the price is very dominant, and the application field is also very wide, including two very hot selling GF50, GF-60, you can click the details page for more technical data. GF50 Single-Axis Medium Accuracy Military Standard Fiber Optic Gyroscope   GF60 Single Axis Fiber Gyro Low Power Fiber Optic Gyro Imu Angular Rate for Navigation  

Key Points Product: High Temperature Accelerometers Key Features: Components: Designed with advanced materials and technologies, such as amorphous quartz structures for enhanced stability. Function: Provide reliable and accurate data in extreme environments, crucial for safety and performance. Applications: Essential in oil & gas (MWD systems), aerospace (structural monitoring), automotive testing (crash and performance assessments), and various industrial sectors. Data Integrity: Capable of operating under high temperatures and vibrations, ensuring continuous performance and minimal downtime. Conclusion: High temperature accelerometers are vital for industries operating in harsh conditions, enhancing efficiency and safety with precise measurements. Reliability is crucial for success in the challenging oil and gas industry, where risks are frequent and can significantly impact opportunities. Dependable, precise data can determine whether a venture succeeds or fails. Ericco has been supplying robust sensing products to the global oil and gas sector, proving their exceptional reliability and accuracy in some of the world’s most demanding environments. 1.What are high temperature accelerometers? High temperature accelerometers are designed to withstand harsh conditions and provide accurate data in demanding industries such as aerospace and oil & gas. Essentially, their purpose is to function effectively in challenging environments, including underground settings and extreme temperatures. Manufacturers of high temperature accelerometers employ specific technologies to ensure the sensors’ reliability in extreme conditions. For instance, Micro-Magic Incs Quartz Accelerometer for Oil and Gas is proved to own high performance. This model utilizes an amorphous quartz proof-mass structure that reacts to acceleration through flexure motion, ensuring excellent stability in bias, scale factor, and axis alignment. 2.How are high temperature accelerometers used? High temperature accelerometers are vital in industries where equipment must endure extreme conditions. Their robust design and advanced technology enable them to operate reliably in harsh environments, providing crucial data that enhances safety, efficiency, and performance. Here’s a closer look at their applications and significance: 2.1 Oil & Gas Industry In the oil & gas industry, high temperature accelerometers are essential components of Measurement While Drilling (MWD) systems. MWD is a well logging technique that uses sensors within the drillstring to provide real-time data, guiding the drill and optimizing drilling operations. These accelerometers can withstand the intense heat, shock, and vibrations encountered deep underground. By delivering accurate measurements, they help. Optimize Drilling Operations: Provide precise data on the drill bit’s orientation and position, aiding in efficient and accurate drilling. Enhance Safety: Detect vibrations and shocks that could indicate potential issues, allowing for timely intervention and prevention of accidents. Improve Efficiency: Reduce downtime by providing continuous, reliable data that helps prevent operational failures and costly interruptions. Fig.1 High Temperature Accelerometers 2.2 Aerospace In the aerospace industry, high temperature accelerometers are used to monitor the performance and structural integrity of aircraft. They can endure the extreme conditions of flight, including high temperatures and intense vibrations, and are crucial for Structural Health Monitoring: Measure vibrations and stresses on aircraft components, ensuring they remain within safe limits. Engine Performance: Monitor vibrations in aircraft engines to detect anomalies and prevent engine failures. Flight Testing: Provide accurate data on aircraft dynamics during test flights, aiding in the development and refinement of aircraft designs. 2.3 Automotive Testing In automotive testing, high temperature accelerometers are employed to measure vehicle dynamics and structural integrity under extreme conditions. They are particularly useful for: Crash Testing: Monitor acceleration and deceleration forces during crash tests to evaluate vehicle safety and crashworthiness.High-Performance Testing: Measure vibrations and stresses in high-performance vehicles to ensure components can withstand extreme driving conditions.Durability Testing: Assess the long-term durability of automotive components by subjecting them to prolonged high temperatures and vibrations. 2.4 Industrial Applications Beyond oil & gas, aerospace, and automotive industries, high temperature accelerometers are also used in various other industrial applications where equipment operates in extreme conditions. These include: Power Generation: Monitor vibrations in turbines and other equipment to ensure optimal performance and prevent failures.Manufacturing: Measure vibrations and stresses in heavy machinery to maintain operational efficiency and safety.Robotics: Provide precise data on the movements and stresses experienced by robots operating in high-temperature environments, such as those used in welding or foundries. 3.Micro-Magic Inc's High Temperature Accelerometers Micro-Magic Inc has excelled in designing and manufacturing high-temperature accelerometers that meet the demanding requirements of these industries. We offer solutions tailored for energy exploration and other high-temperature applications. These accelerometers feature: Analog Output: For easy integration with existing systems.Mounting Options: Square or round flanges to suit different installation needs.Field-Adjustable Range: Allowing customization to specific application requirements.Internal Temperature Sensors: For thermal compensation, ensuring accurate measurements despite temperature variations. What’s more, Micro-Magic Inc’s Quartz Accelerometer for Oil and Gas is proved to own high performance. This model utilizes an amorphous quartz proof-mass structure that reacts to acceleration through flexure motion, ensuring excellent stability in bias, scale factor, and axis alignment. Some high temperature accelerometers also incorporate external amplifiers to safeguard the sensor from heat damage. And we recommend the AC1 for oil and gas, whose operating temperature is -55 ~ +85 ℃, with an input range of ±50g, bias repeatability <30μg, and scale factor repeatability <50 ppm. 4.Conclusion High temperature accelerometers are indispensable in industries that operate under extreme conditions. Their ability to provide reliable and accurate data in such environments enhances operational efficiency, safety, and performance. With advancements in technology, these sensors continue to evolve, offering even greater reliability and precision in the most demanding applications. AC1 Navigation Class Level Quartz Flexible Accelerometer With Measurement Range 50G Excellent Long-Term Stability And Repeatability   AC2 50 G Quartz Flexure Accelerometer Quartz Pendulous Accelerometers Inertial Navigation