MEMS gyroscope array error suppression device and method based on active piezoelectric excitation

Abstract

The application relates to a MEMS gyro array error suppression device and method based on active piezoelectric excitation. The MEMS gyro array error suppression device and method based on active piezoelectric excitation designed by the application applies controlled low-frequency micro-amplitude mechanical vibration to the MEMS gyro array through a piezoelectric exciter, physically modulates the internal resonance state of the gyroscope to reduce the time correlation of the scale factor error, and converts systematic deviation into random noise. In combination with a base matched in terms of thermal expansion coefficient and double-mode signal processing, the device can separate effective signals while suppressing thermal stress interference, so that the array fusion algorithm can eliminate common-mode errors, and the measurement precision is improved to within 0.5 degrees without changing the sensor process.

Description

Technical Field

[0001] This application relates to the field of microelectromechanical systems (MEMS) sensor technology, and in particular to a MEMS gyroscope array error suppression device and method based on active piezoelectric excitation. Background Technology

[0002] In existing technologies, MEMS gyroscopes are widely used in navigation systems due to their advantages such as small size and low cost. However, their performance is limited by various error sources, especially scale factor error and bias error. These errors typically have time and spatial correlations (such as temperature drift and mechanical coupling), leading to error superposition when multiple gyroscope arrays are fused, which significantly reduces the system accuracy. For example, in downhole north-finding applications, the north-finding error of traditional MEMS gyroscope arrays is generally between 1° and 2°, which is difficult to meet the high-precision requirements.

[0003] Traditional MEMS gyroscopes have a strong correlation between scale factor error and manufacturing process and environmental factors (such as temperature and vibration), which leads to error accumulation and decreased accuracy during array fusion.

[0004] Currently, technologies for improving the performance of MEMS gyroscopes are mainly divided into two categories: one is the circuit correction method, such as in patent CN111780735A, which adjusts the amplitude or frequency of the drive signal through a feedback circuit, but it can only suppress a single error source and cannot solve the error correlation between multiple gyroscopes; the other is the structural optimization method, such as in patent CN103234536A, which designs a multi-degree-of-freedom resonant structure to reduce modal coupling, but the process is complex and the environmental adaptability is poor. Summary of the Invention

[0005] To address the aforementioned issues, this application provides a MEMS gyroscope array error suppression device and method based on active piezoelectric excitation to improve the accuracy of low-cost MEMS gyroscope arrays under complex operating conditions.

[0006] To achieve the above objectives, in a first aspect, embodiments of this application provide a MEMS gyroscope array error suppression device based on active piezoelectric excitation, comprising: Base; MEMS gyroscope array, comprising multiple MEMS gyroscopes mounted on the base in a preset layout for detecting angular velocity signals; A piezoelectric excitation module, mechanically coupled to the base or the MEMS gyroscope array, is used to apply modulated vibrations to the MEMS gyroscope array; The control and processing system is configured to control the piezoelectric excitation module to generate the modulated vibration in order to reduce the correlation of scaling factor errors among the MEMS gyroscopes in the MEMS gyroscope array; and to receive the output signals of multiple MEMS gyroscopes and calculate the target angular velocity using an array fusion algorithm.

[0007] Preferably, the base is made of aluminum nitride ceramic material, whose coefficient of thermal expansion matches that of the chip material of the MEMS gyroscope; the excitation direction of the piezoelectric excitation module forms a 45-degree coupling angle with the sensitive axis of the MEMS gyroscope.

[0008] Preferably, the control processing system includes a vibration control circuit, which adjusts the piezoelectric excitation module based on a digital PID closed-loop control algorithm, and its control transfer function... As shown in the following formula: Among them, K p K i K d These are the proportional, integral, and differential gain coefficients, respectively, and s is a complex variable. By adjusting the gain coefficients, the frequency of the modulated vibration is locked within the range of 1Hz to 10Hz, and the vibration acceleration amplitude is locked within the range of less than 0.1g.

[0009] Preferably, the frequency ω and amplitude A of the modulated vibration are determined by solving a model that minimizes the error correlation coefficient, and the objective function of the model is as follows: Where ρ is the error correlation coefficient, N is the number of gyroscopes, and SF i Let ε be the scaling factor of the i-th gyroscope in the excited state. i Let be the error term of the i-th gyroscope.

[0010] Preferably, the control processing system extracts the characteristic signal of the modulated vibration using the lock-in amplification principle shown in the following formula for vibration state monitoring: Among them, V out To monitor the output amplitude, For the reference signal amplitude, Let X be the phase difference, and let Y be the in-phase component and quadrature component of the input signal, respectively.

[0011] Secondly, this application provides a method for suppressing errors in a MEMS gyroscope array based on active piezoelectric excitation, comprising the following steps: Step S1: Applying micro-amplitude mechanical vibration with a frequency below 10Hz to the MEMS gyroscope array through a piezoelectric exciter; Step S2: Disrupting the internal resonance state of the MEMS gyroscope by the micro-amplitude mechanical vibration, thereby destroying the time correlation of the scaling factor error; Step S3: Synchronously acquiring the output signals of each gyroscope in the MEMS gyroscope array; Step S4: Decoupling and array fusion calculations are performed on the acquired output signals to output high-precision angular velocity data.

[0012] Preferably, in step S4, the array fusion calculation employs a weighted average fusion algorithm, where the output weights w of each gyroscope are... i The calculation formula is as follows: in, Let i be the output angular velocity of the i-th gyroscope. Let be the real-time noise variance of the i-th gyroscope, and N be the total number of gyroscopes.

[0013] Preferably, in step S4, the array fusion calculation employs the extended Kalman filter algorithm, and its state equation and observation equation are as follows: in This is a state vector containing the true value of the angular velocity and the zero bias. Here is the state transition matrix. For the observation matrix, and These are the process noise vector and the observation noise vector, respectively.

[0014] Preferably, the extended Kalman filter algorithm utilizes the state covariance matrix. The update process includes the following formulas: in, Here is the Kalman gain matrix. To predict the covariance matrix.

[0015] Preferably, the piezoelectric actuator in step S1 is made of PZT-5H piezoelectric ceramic material, and its electromechanical coupling coefficient k 31 ≥0.65, and the micro-amplitude mechanical vibration is transmitted to the MEMS gyroscope array through an aluminum nitride base.

[0016] The MEMS gyroscope array error suppression device and method designed in this application, based on active piezoelectric excitation, applies controlled low-frequency micro-amplitude mechanical vibration to the MEMS gyroscope array through a piezoelectric exciter. This physically modulates the internal resonant state of the gyroscope to reduce the time correlation of scaling factor error, converting systematic deviations into random noise. Combined with a base matching the coefficient of thermal expansion and dual-mode signal processing, this device separates effective signals while suppressing thermal stress interference, enabling the array fusion algorithm to eliminate common-mode errors and improve measurement accuracy to within 0.5° without changing the sensor manufacturing process. Attached Figure Description

[0017] Figure 1 This application provides a MEMS gyroscope array error suppression device and method based on active piezoelectric excitation.

[0018] Figure 2 This is a flowchart illustrating the MEMS gyroscope array error suppression method based on active piezoelectric excitation provided in the embodiments of this application.

[0019] The system includes: base 10, MEMS gyroscope 20, piezoelectric exciter 30, and control and processing system 40. Detailed Implementation

[0020] The preferred embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application.

[0021] In a first aspect, embodiments of this application provide a MEMS gyroscope array error suppression device based on active piezoelectric excitation. This device adopts a hardware-software co-engineering architecture that combines physical intervention with algorithmic integration. (See reference...) Figure 1 It mainly includes a high-rigidity base 10, a ring-shaped redundant MEMS gyroscope array, a piezoelectric excitation module, and a control and processing system 40.

[0022] Specifically, the base 10 is preferably made of aluminum nitride (AlN) ceramic material, and the coefficient of thermal expansion (CTE) of aluminum nitride is approximately 4.6 × 10⁻⁶. −6 / ℃, this value is highly matched with the thermal expansion coefficient of the core sensing chip of the MEMS gyroscope 20, which is usually made of silicon. This material-level matching design can eliminate the additional thermal stress generated by ambient temperature fluctuations at the contact surface between the sensor and the base 10 from the physical source, ensuring that the vibration energy of piezoelectric excitation is purely transferred to the gyroscope resonant structure. This can effectively solve the problem of thermal drift of MEMS gyroscope 20 in environments such as underground high temperature (e.g., 85℃) and vibration environments.

[0023] The piezoelectric excitation module is mechanically coupled to the base 10 or the MEMS gyroscope array to apply modulated vibrations to the MEMS gyroscope array. Specifically, during the hardware assembly stage, the piezoelectric excitation module uses a high-performance PZT-5H piezoelectric ceramic actuator, which has excellent electromechanical coupling characteristics (electromechanical coupling coefficient k31 ≥ 0.65) and a high Curie temperature (T). c (≥250℃), and use epoxy resin adhesive to cure the piezoelectric ceramic actuator onto the base 10 with high strength to ensure the long-term stability of mechanical coupling.

[0024] Furthermore, to achieve balanced interference against multi-axis errors, the excitation direction of the piezoelectric excitation module forms a 45° coupling angle with the sensitive axis of the MEMS gyroscope 20. This angle design can effectively decompose unidirectional vibration energy into orthogonal components, while simultaneously modulating the driving and detection modes of the gyroscope.

[0025] The MEMS gyroscope array comprises N units, preferably 6 or 8 MEMS gyroscopes 20 in this embodiment, which are mounted on the base 10 in a pre-defined circular symmetrical layout for detecting angular velocity signals. During installation, the sensitive axis of each gyroscope is adjusted using a high-precision laser calibrator to ensure it is strictly aligned on the same horizontal plane, and the installation angle error between adjacent gyroscopes is controlled within ±0.1°. This high-precision geometric calibration reduces the impact of installation errors on the subsequent array fusion accuracy.

[0026] In this embodiment, the control processing system 40 is configured to control the piezoelectric excitation module to generate the modulated vibration in order to reduce the correlation of scaling factor errors among the MEMS gyroscopes 20 in the MEMS gyroscope array; and to receive the output signals of the multiple MEMS gyroscopes 20 and calculate the target angular velocity using an array fusion algorithm.

[0027] In practical implementation, to generate stable and controllable uncorrelated vibration signals, the control processing system 40 embeds a precision vibration control circuit. This vibration control circuit adjusts the piezoelectric excitation module based on a digital PID closed-loop control algorithm, and its control transfer function... As shown in the following formula: Among them, K p K i K d These are the proportional, integral, and differential gain coefficients, respectively, and s is a complex variable. In some embodiments, K... p =1.2, K i =0.05, K d=0.01. By adjusting the gain coefficient, the frequency of the micro-amplitude modulated vibration can be strictly locked within a low-frequency range of 1Hz to 10Hz, preferably 10Hz in this embodiment; and the vibration acceleration amplitude can be locked within a microgravity range of less than 0.1g, preferably 0.05g-0.1g. This parameter setting is sufficient to interfere with the formation of scaling factor error without causing gyroscope output overload or physical damage.

[0028] In some embodiments, the control processing system 40 extracts the characteristic signal of the modulated vibration using the lock-in amplification principle shown in the following formula to monitor the vibration state: Among them, V out To monitor the output amplitude, For the reference signal amplitude, Let X and Y be the phase difference, and X and Y be the in-phase and quadrature components of the input signal, respectively. Thus, by monitoring V... out The stability of the piezoelectric element can be used to determine whether it is aging or loose, and to compensate for it.

[0029] In some embodiments, to maximize the effect of error decorrelation, the device performs a parameter optimization process during the initialization phase. The frequency ω and amplitude A of the modulated vibration are determined by solving a model that minimizes the error correlation coefficient. The objective function of the model is as follows: Where ρ is the error correlation coefficient, N is the number of gyroscopes, and SF i Let ε be the scaling factor of the i-th gyroscope in the excited state. i Let ρ be the error term of the i-th gyroscope. Thus, by sweeping the frequency test to make ρ approach 0, the systematic error is physically transformed into random noise, creating a prerequisite for subsequent algorithm processing.

[0030] Secondly, embodiments of this application provide a method for suppressing errors in a MEMS gyroscope array based on active piezoelectric excitation. Based on the same concept, taking the processing flow of high-precision angular velocity measurement using the device described in the first aspect embodiment as an example, see [link to relevant documentation]. Figure 2 The method mainly includes the following steps: Step S1: Apply micro-amplitude mechanical vibration with a frequency below 10Hz to the MEMS gyroscope array through the piezoelectric exciter 30.

[0031] In practice, a defined low-frequency (<10Hz) micro-amplitude vibration is applied to the MEMS gyroscope array via the piezoelectric exciter 30, while the control processing system 40 employs dual-channel time-frequency joint processing. Excitation channel: Focuses on extracting 10Hz vibration characteristics for closed-loop control.

[0032] Navigation Channel: Known 10Hz excitation signals are removed using notch filters or low-pass filters, retaining the frequency band signal containing true angular velocity information. Since the excitation signal is actively generated by the system and has complete observability and controllability, it can be perfectly stripped without losing navigation information.

[0033] Step S2: Disrupt the resonant state inside the MEMS gyroscope 20 by interfering with the micro-amplitude mechanical vibration, thereby disrupting the time correlation of the scaling factor error.

[0034] Specifically, the micro-amplitude mechanical vibration is transmitted through the aluminum nitride (AlN) ceramic base 10, which interferes with the stress distribution of the internal resonant structure of the MEMS gyroscope 20, destroys the time correlation of the scaling factor error as it slowly drifts over time, and whitens it into statistically random noise.

[0035] Step S3: Synchronously acquire the output signals of each gyroscope in the MEMS gyroscope array.

[0036] Step S4: Decouple the acquired output signal and perform array fusion calculation to output high-precision angular velocity data.

[0037] In practice, the decoupled output signals of each channel are collected synchronously, and the array fusion algorithm is adaptively selected based on the real-time monitored environmental noise level. Scenario A (Low Noise / Stable Operating Condition): Weighted Average Fusion Algorithm When the environment is stable, a weighted average method is used to reduce computational power consumption. The output weights w of each gyroscope are... i The calculation formula is as follows: in, Let i be the output angular velocity of the i-th gyroscope. Let be the real-time noise variance of the i-th gyroscope, and N be the total number of gyroscopes. Devices with higher noise levels are assigned lower weights.

[0038] Scenario B (High Noise / Dynamic North Finding): Extended Kalman Filter Algorithm When the environment is complex or precise north-finding is required, the system switches to Extended Kalman Filter (EKF).

[0039] Establish the state equations: ; Establish the observation equation: .

[0040] in This is a state vector containing the true value of the angular velocity and the zero bias. Here is the state transition matrix. For the observation matrix, and These are the process noise vector and the observation noise vector, respectively.

[0041] Using the state covariance matrix The update process includes the following formulas: in, Here is the Kalman gain matrix. To predict the covariance matrix.

[0042] Thanks to the physical decorrelation processing in steps S1-S2, the observation noise vector r k The covariance matrix tends to be a diagonal matrix, which satisfies the optimal estimation condition of Kalman filtering, thus enabling the accurate extraction of the true signal from the noise.

[0043] In some embodiments, the method further includes the step of: if a strong external impact is detected, the processing control system will temporarily reduce or turn off the piezoelectric excitation amplitude to prevent the active excitation from being superimposed with the external impact and causing the sensor to overload, and automatically restore to the preset optimized excitation parameters after the impact disappears.

[0044] The MEMS gyroscope array error suppression device and method based on active piezoelectric excitation provided in this application applies controlled low-frequency micro-amplitude mechanical vibration to the MEMS gyroscope array through a piezoelectric exciter 30. This physically modulates the internal resonant state of the gyroscope to reduce the time correlation of scaling factor error, converting systematic deviations into random noise. Combined with a thermally matched base 10 and dual-mode signal processing, this device separates effective signals while suppressing thermal stress interference, enabling the array fusion algorithm to eliminate common-mode errors and improve measurement accuracy to within 0.5° without changing the sensor manufacturing process.

[0045] In the description of this application, it should be noted that the terms "vertical", "up", "down", "horizontal", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0046] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0047] Finally, it should be noted that the above descriptions are merely preferred embodiments of this application and are not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A MEMS gyroscope array error suppression device based on active piezoelectric excitation, characterized in that, include: Base; MEMS gyroscope array, comprising multiple MEMS gyroscopes mounted on the base in a preset layout for detecting angular velocity signals; A piezoelectric excitation module, mechanically coupled to the base or the MEMS gyroscope array, is used to apply modulated vibrations to the MEMS gyroscope array; The control processing system is configured to control the piezoelectric excitation module to generate the modulated vibration in order to reduce the correlation of scaling factor errors among the MEMS gyroscopes in the MEMS gyroscope array; It is configured to receive the output signals of multiple MEMS gyroscopes and calculate the target angular velocity using an array fusion algorithm.

2. The MEMS gyroscope array error suppression device based on active piezoelectric excitation according to claim 1, characterized in that, The base is made of aluminum nitride ceramic material, whose coefficient of thermal expansion matches that of the MEMS gyroscope chip material; the excitation direction of the piezoelectric excitation module forms a 45-degree coupling angle with the sensitive axis of the MEMS gyroscope.

3. The MEMS gyroscope array error suppression device based on active piezoelectric excitation according to claim 1, characterized in that, The control processing system includes a vibration control circuit, which adjusts the piezoelectric excitation module based on a digital PID closed-loop control algorithm. Its control transfer function... As shown in the following formula: Among them, K p K i K d These are the proportional, integral, and differential gain coefficients, respectively, and s is a complex variable. By adjusting the gain coefficients, the frequency of the modulated vibration is locked within the range of 1Hz to 10Hz, and the vibration acceleration amplitude is locked within the range of less than 0.1g.

4. The MEMS gyroscope array error suppression device based on active piezoelectric excitation according to claim 1, characterized in that, The frequency ω and amplitude A of the modulated vibration are determined by solving a model that minimizes the error correlation coefficient. The objective function of the model is as follows: Where ρ is the error correlation coefficient, N is the number of gyroscopes, and SF i Let ε be the scaling factor of the i-th gyroscope in the excited state. i Let be the error term of the i-th gyroscope.

5. The MEMS gyroscope array error suppression device based on active piezoelectric excitation according to claim 1, characterized in that, The control and processing system extracts the characteristic signal of the modulated vibration using the lock-in amplification principle shown in the following formula for vibration state monitoring: Among them, V out To monitor the output amplitude, For the reference signal amplitude, Let X be the phase difference, and let Y be the in-phase component and quadrature component of the input signal, respectively.

6. A method for suppressing errors in a MEMS gyroscope array based on active piezoelectric excitation, characterized in that, Includes the following steps: Step S1: Apply micro-amplitude mechanical vibration with a frequency below 10Hz to the MEMS gyroscope array via a piezoelectric exciter; S2: Disrupt the internal resonance state of the MEMS gyroscope by the micro-amplitude mechanical vibration, thereby destroying the time correlation of the scaling factor error; S3: Synchronously acquire the output signals of each gyroscope in the MEMS gyroscope array; S4: Decouple and perform array fusion calculation on the acquired output signals to output high-precision angular velocity data.

7. The MEMS gyroscope array error suppression method based on active piezoelectric excitation according to claim 6, characterized in that, In step S4, the array fusion calculation employs a weighted average fusion algorithm, with each gyroscope's output weight w i The calculation formula is as follows: in, Let i be the output angular velocity of the i-th gyroscope. Let be the real-time noise variance of the i-th gyroscope, and N be the total number of gyroscopes.

8. The MEMS gyroscope array error suppression method based on active piezoelectric excitation according to claim 6, characterized in that, In step S4, the array fusion calculation employs the extended Kalman filter algorithm, and its state equation and observation equation are as follows: in This is a state vector containing the true value of the angular velocity and the zero bias. Here is the state transition matrix. For the observation matrix, and These are the process noise vector and the observation noise vector, respectively.

9. The MEMS gyroscope array error suppression method based on active piezoelectric excitation according to claim 8, characterized in that, The extended Kalman filter algorithm utilizes the state covariance matrix. The update process includes the following formulas: in, Here is the Kalman gain matrix. To predict the covariance matrix.

10. The MEMS gyroscope array error suppression method based on active piezoelectric excitation according to claim 6, characterized in that, The piezoelectric actuator in step S1 is made of PZT-5H piezoelectric ceramic material, and its electromechanical coupling coefficient k 31 ≥0.65, and the micro-amplitude mechanical vibration is transmitted to the MEMS gyroscope array through an aluminum nitride base.

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