Design and Experiment for Dual-Mass MEMS Gyroscope Sensing Closed-Loop System

Cao, Huiliang; Xue, Rihui; Cai, Qi; Gao, Jinyang; Zhao, Rui; Shi, Yunbo; Huang, Kun; Shao, Xingling; Shen, Chong

doi:10.1109/access.2020.2977223

Cited by 30 publications

(19 citation statements)

References 35 publications

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“…There are related simulations of the first four sequential modes in Ansys soft, as shown in Figure 2. In practice, the drive mode shows purely anti-phase mode drive, it is for three main reasons: the relevant excitation mode of the drive mode, the quality factor Rx2 of the anti-phase drive mode is greater than 2000, the frequency difference between the anti-phase mode and the in phase mode is more than 1000Hz., Since the actual sensing mode used for work consists of the second and the third mode, the motion equation of gyroscope structure can be expressed by Equation (1) in ideal case: (1) where, S = [x,y1,y2] T is the displacement, m = [mx,my,my] T is the mass, = [ , , ]…”

Section: Gyro Structurementioning

confidence: 99%

“…The MEMS gyroscope based on Coriolis acceleration mainly conveys vibration between the drive mode and the detection mode [1,2], due to its advantages such as robustness, low noise, and low power consumption [3], MEMS technology and gyroscopes have been widely used in aviation, aerospace, measuring and other important fields [4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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A Temperature Error Parallel Processing Model for MEMS Gyroscope based on a Novel Fusion Algorithm

Cao

Shen

2020

Electronics

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To deal with the influence of temperature drift for a Micro-Electro-Mechanical System (MEMS) gyroscope, this paper proposes a new temperature error parallel processing method based on a novel fusion algorithm. Firstly, immune based particle swarm optimization (IPSO) is employed for optimal parameters search for Variational Modal Decomposition (VMD). Then, we can get the optimal decomposition parameters, wherein permutation entropy (PE) is employed as the fitness function of the particles. Then, the improved VMD is performed on the output signal of the gyro to obtain intrinsic mode functions (IMFs). After judging by sample entropy (SE), the IMFs are divided into three categories: noise term, mixed term and feature term, which are processed differently. Filter the mixed term and compensate the feature term at the same time. Finally, reconstruct them and get the result. Compared with other optimization algorithms, IPSO has a stronger global search ability and faster convergence speed. After Back propagation neural network (BP) is enhanced by Adaptive boosting (Adaboost), it becomes a strong learner and a better model, which can approach the real value with higher precision. The experimental result shows that the novel parallel method proposed in this paper can effectively solve the problem of temperature errors.Electronics 2020, 9, 499 2 of 21 circuit design structure to reduce the damping coefficient, which is convenient and economical [15]. Yang et al. adopted a new concept whereby the on-chip temperature compensation of the MEMS gyroscope is realized by the on-chip sensor. In order to make the on-chip temperature of the micro gyroscope well controlled, the newly integrated serpentine micro heater is used to achieve this function [16]. Cui et al. analyzed the working principle of the gyroscope and adopted the vibration compensation of the drive mode, which has a good effect [17]. However, the hardware compensation cost is high and it is too difficult to implement.The second is through software compensation, it includes the removal of noise and temperature compensation. The software compensation method mainly establishes a model for the drift part and the noise part of the MEMS gyroscope to remove noise and compensate drift. For the establishment of the temperature drift model, the reference temperature and the corresponding temperature drift output obtained in advance are used as a set of training set data. The model is established after the learning and training of the algorithm. When the temperature value is input, the model can predict the output value as compensation. There are two main methods. The first one is serial processing, which first uses a filter to perform noise reduction on the signal and then uses a model to eliminate drift. The other one is parallel processing, which refers to extracting and processing noise components and drift components separately. Dominik uses a combination of experiments and numerical values to provide accurate ceramic acceleration at higher temperature [18]. Yang uses a sim...

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Section: Gyro Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Temperature Error Parallel Processing Model for MEMS Gyroscope based on a Novel Fusion Algorithm

Cao

Shen

2020

Electronics

Self Cite

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“…and using (11) in (10) yields (17). In order to avoid the random loss of measurement in calculating the Kalman gain K which introduces more errors, the first moments instead of measurements is used to determine the Kalman gain.…”

Section: ) Variational Bayesian Measurement Updatementioning

confidence: 99%

“…▪ Initialization by using (13) ▪ Update the state vector by using (15)- (17) ▪ Update the scale matrices (…”

Section: Variational Bayesian Measurement Updatementioning

confidence: 99%

A Novel Nonlinear Algorithm for Non-Gaussian Noises and Measurement Information Loss in Underwater Navigation

et al. 2020

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The ocean environment is complex and changeable because of all kinds of noise interferences, such as salt cliffs, ships around and other electromagnetic interferences, so the measurement information is prone to be lost. It is difficult to describe the complex noise and the acquisition probability of measurement information. In this paper, a continuous discrete variational Bayesian filter (CD VBF) is proposed to solve the problems of the heavy tailed noises and measurement random loss for state estimation. The variational Bayesian (VB) approach can effectively estimate the state vector, scale matrices, degree of freedom (DOF) parameters, Bernoulli random variables and the acquisition probability of measurement information. The performances of the proposed algorithm and traditional algorithms are tested in simulations and underwater experiments. The simulation results illustrate that the CD VBF has better localization accuracy and robustness. The experimental results demonstrate that the localization accuracy is improved by CD VBF and an optimal solution of iteration number is acquired.

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“…The right and left sense frame movement signals were detected with the differential detection amplifier, while a second differential amplifier processed the output signal, in order to generate the sensing mode movement signal V stotal . To acquire the sense mode movement signal, V stotal was demodulated by V dac Sin(w d t) and, then, a low-pass filter was configured to eliminate the noise [28].…”

Section: The Introduction Of the Gyroscope Monitoring Systemmentioning

confidence: 99%

Dual-Mass MEMS Gyroscope Parallel Denoising and Temperature Compensation Processing Based on WLMP and CS-SVR

2020

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For the sake of decreasing the effects of noise and temperature error on the measurement accuracy of micro-electro-mechanical system (MEMS) gyroscopes, a denoising and temperature drift compensation parallel model method based on wavelet transform and forward linear prediction (WFLP) and support vector regression based on the cuckoo search algorithm (CS-SVR) is proposed in this paper. First, variational mode decomposition (VMD) is proposed in this paper, which is aimed at dividing the output signal of the gyroscope into intrinsic mode functions (IMFs); then, the IMFs are classified into three features—drift, mixed, and pure noise features—by the sample entropy (SE) value. Second, a wavelet transform and forward linear prediction (WFLP) are combined to remove the noise from the mixed features. Meanwhile, the drift feature is compensated by support vector regression based on the cuckoo search algorithm (CS-SVR). Finally, through reconstruction, the final signal is obtained. Experimental results demonstrate that the VMD-SE-WFLP-CS-SVR method proposed in this paper can decrease noise and compensate the temperature error effectively (angular random walking value is optimized from 1.667°/√h to 0.0667°/√h and the bias stability is reduced from 30°/h to 4°/h). In terms of denoising, the performance of the WFLP algorithm is superior to the wavelet threshold and FLP, as it combines their advantages; furthermore, in terms of temperature compensation, the proposed CS-SVR algorithm uses the cuckoo search algorithm to find the optimal parameters of SVR, improving the accuracy of the model.

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Design and Experiment for Dual-Mass MEMS Gyroscope Sensing Closed-Loop System

Cited by 30 publications

References 35 publications

A Temperature Error Parallel Processing Model for MEMS Gyroscope based on a Novel Fusion Algorithm

A Temperature Error Parallel Processing Model for MEMS Gyroscope based on a Novel Fusion Algorithm

A Novel Nonlinear Algorithm for Non-Gaussian Noises and Measurement Information Loss in Underwater Navigation

Dual-Mass MEMS Gyroscope Parallel Denoising and Temperature Compensation Processing Based on WLMP and CS-SVR

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