A temperature characteristic research and compensation design for micro-machined gyroscope

Fu, Qiang; Di, Xinpeng; Chen, Weiping; Yin, Liang; Liu, Xiaowei

doi:10.1142/s0217984917500646

Cited by 16 publications

(14 citation statements)

References 5 publications

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“…In AGC loop, the vibration amplitude is intended to be stabilised at the resonant amplitude in (2), while in fact we can only keep the extracted amplitude as a constant A ref , which means the authentic vibration amplitude might be out of control when temperature varies. For TEB method, the actual vibration amplitude after AGC can be given in the following form as (7), and for linear-EAM method as (8)…”

Section: Gyroscope Dynamicsmentioning

confidence: 99%

Temperature‐dependence improvement for a MEMS gyroscope using triangular‐electrode based capacitive detection method

Lin

Zheng

Liu

et al. 2017

Micro & Nano Letters

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This work presents analysis and test results on temperature-dependence improvement for a microelectromechanical systems (MEMS) gyroscope based on triangular-electrode based (TEB) capacitive detection method. To reduce the effects of temperature variations on MEMS gyroscopes, TEB capacitive detection method is applied because the extracted amplitude and phase are robust to system parameter fluctuations. In the first place, analytical results for the scale factors and zero-rate outputs, respectively, utilising linear electromechanical amplitude modulation (linear-EAM) method and TEB method are derived. Then experimental results of the temperature characteristics for gyroscopes are conducted. The temperature coefficient of scale factor over the temperature range of −10 to 60°C is reduced from −8845 ppm/°C for linear-EAM method to 1660 ppm/°C for TEB method with an improvement factor of 5.3. Moreover, the temperatureinduced zero-rate output variation is decreased from −68.05°/s for linear-EAM method to −29.09°/s for TEB method with an improvement factor of 2.3. Experimental results of temperature-dependence improvement agree well with the theoretical analysis. In the end, Allan variance analysis demonstrates a bias instability of 2.85°/h, and an ARW (angle random walk) of 0.16°/√h with a vacuumpackaged gyroscope using TEB method, which is significantly better than the bias instability 5.47°/h and ARW 0.22°/√h tested using linear-EAM method.

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Section: Gyroscope Dynamicsmentioning

confidence: 99%

Temperature‐dependence improvement for a MEMS gyroscope using triangular‐electrode based capacitive detection method

Lin

Zheng

Liu

et al. 2017

Micro & Nano Letters

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“…For example, the robust structural design of MEMS vibratory gyroscopes is proposed in [3] to compensate for temperature effects drift. In [4], it decreases the effects of the damping coefficient and resonant frequency by designing an effective circuit. Gyroscope researches use a lot of hardware compensation, however, it is expensive and cumbersome to operate.…”

Section: Introductionmentioning

confidence: 99%

A Parallel Denoising Model for Dual-Mass MEMS Gyroscope Based on PE-ITD and SA-ELM

Cao

et al. 2019

IEEE Access

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In a bid to solve the gyroscope temperature drift problem, a parallel denoising model based on PE-ITD and SA-ELM has been proposed in this paper, wherein, Intrinsic timescale decomposition (ITD) is an effective signal decomposition algorithm, Permutation entropy (PE) is a entropy to accurately determine the complexity of the signal, Extreme Learning machine (ELM) is a machine learning algorithm for predicting, and Simulated Annealing(SA) for finding the optimal parameter set. First, ITD is employed to decompose the output signal of the gyroscope and the PE can distinguish the decomposition results into noise-only component, mixed component and trend component. Secondly, the mixed component is filtered by Forward liner prediction (FLP), the denoised signal can be obtained after processing. Finally, the trend component is compensated by SA-ELM, through reconstruction, the compensation result can be obtained. As is shown in experimental results, the parallel model proposed in this paper is able to effectively eliminate the temperature error compared with the traditional serial model. Compared with the EMD analysis method, the ITD is superior to the EMD analysis method in terms of computational efficiency and instantaneous information. The proposed SA-ELM algorithm takes simulated annealing algorithm to find hidden layer neurons' optimal number adaptively, which can improve the model's accuracy and generalization. This paper demonstrates the superiority of this method.

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“…Cao et al established a new silicon structure equivalent electric model in order to improve the accuracy of performance under higher temperature [14]. Fu et al proposed a simpler and more applicable compensation method which is provided with a new circuit to reduce the influence of damping coefficient and resonating frequency [15]. Yang et al proposed an architecture that utilizes the on-chip temperature sensor of the micro-Gyro to achieve the onchip temperature compensation and used the integrated serpentine microheater to realize the on-chip temperature control of the micro-Gyro [16].…”

Section: Introductionmentioning

confidence: 99%

Temperature Energy Influence Compensation for MEMS Vibration Gyroscope Based on RBF NN‐GA‐KF Method

Cao

Zhang

Shen

et al. 2018

Shock and Vibration

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This paper proposed three methods to compensate the temperature energy influence drift of the MEMS vibration gyroscope, including radial basis function neural network (RBF NN), RBF NN based on genetic algorithm (GA), and RBF NN based on GA with Kalman filter (KF). Three-axis MEMS vibration gyroscope (Gyro X, Gyro Y, and Gyro Z) output data are compensated and analyzed in this paper. The experimental results proved the correctness of these three methods, and MEMS vibration gyroscope temperature energy influence drift is compensated effectively. The results indicate that, after RBF NN-GA-KF method compensation, the bias instability of Gyros X, Y, and Z improves from 139°/h, 154°/h, and 178°/h to 2.9°/h, 3.9°/h, and 1.6°/h, respectively. And the angle random walk of Gyros X, Y, and Z was improved from 3.03°/h1/2, 4.55°/h1/2, and 5.89°/h1/2to 1.58°/h1/2, 2.58°/h1/2, and 0.71°/h1/2, respectively, and the drift trend and noise characteristic are optimized obviously.

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A temperature characteristic research and compensation design for micro-machined gyroscope

Cited by 16 publications

References 5 publications

Temperature‐dependence improvement for a MEMS gyroscope using triangular‐electrode based capacitive detection method

Temperature‐dependence improvement for a MEMS gyroscope using triangular‐electrode based capacitive detection method

A Parallel Denoising Model for Dual-Mass MEMS Gyroscope Based on PE-ITD and SA-ELM

Temperature Energy Influence Compensation for MEMS Vibration Gyroscope Based on RBF NN‐GA‐KF Method

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