Nonlinearity measurement for low-pressure encapsulated MEMS gyroscopes by transient response

Wei, Yumiao; Dong, Yonggui; Huang, Xianxiang

doi:10.1016/j.ymssp.2017.07.034

Cited by 13 publications

(3 citation statements)

References 21 publications

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“…Therefore, in the next study, there are many studies on the solution methods, but the dominant ones are the harmonic balance method [ 13 ], multiscale method [ 14 ], Chebyshev polynomials [ 15 ], and KBM method [ 16 ]. With the help of these methods, the influence of the nonlinear vibration can be seen directly by analyzing the dynamic performance with stability lobe graphs [ 17 ] or measurement experiments [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

A Compensation Method for Nonlinear Vibration of Silicon-Micro Resonant Sensor

Xiao

et al. 2021

Sensors

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A compensation method for nonlinear vibration of a silicon micro resonant sensor is proposed and evaluated to be effective through simulation and experimental analysis. Firstly, the parameter characterization model of the silicon micro resonant sensor is established, which presents significant nonlinearity because of the nonlinear vibration of the resonant beam. A verification circuit is devised to imitate the nonlinear behavior of the model by matching the simulation measurement error of the frequency offset produced by the circuit block with the theoretical counterparts obtained from the model. Secondly, the principle of measurement error compensation is studied, and the compensation method dealing with nonlinear characteristics of the resonant beam is proposed by introducing a compensation beam and corresponding differential operations. The measurement error, compensation rate, and measurement residual between the two scenarios that use single beam and double beams, respectively, are derived and are compared with their simulation and experimental counterparts. The results coincide with the predicted trend, which verifies the effectiveness of the compensation method.

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Section: Introductionmentioning

confidence: 99%

A Compensation Method for Nonlinear Vibration of Silicon-Micro Resonant Sensor

Xiao

et al. 2021

Sensors

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“…For these reasons, alternatives to such methods have been presented [ 21 , 22 ]. The application of such a method to nonlinear MEMS resonators as presented in [ 23 ], and remains the exception. Accordingly, characterization methods that reduce the impact of hysteresis are not widely employed in the literature touching on the design and development of nonlinear MEMS resonators, as can be observed in [ 6 , 7 , 8 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 24 , 25 , 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Control of Spring Softening and Hardening in the Squared Daisy

et al. 2021

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Nonlinear, mechanical microelectromechanical system (MEMS) resonating structures exhibit large displacement and a relatively broad operating bandwidth. These unique features make them particularly of interest for the development of MEMS actuators and sensors. In this work, a mechanical MEMS structure allowing the designer to determine the type of nonlinearity, that is, softening or hardening, based on its anchor scheme is presented. Effects of the excitation signal on the behavior of the proposed MEMS in the frequency domain are investigated. In this regard, a comprehensive experimental comparison among the nonlinear behaviors of softening and hardening has been conducted. To reduce the hysteresis effect to a minimum, an excitation approach, which is a pulsed sweep in frequency with a discrete resolution, is presented. The maximal velocity, quality factor, bandwidth, and resonant frequency of these two types of nonlinear MEMS resonators are compared under three different types of excitation. Finally, it is shown that the performance and characteristics extracted from nonlinear mechanical MEMS resonating structures are highly dependent on the excitation method. Hence, in the present case, the apparent performances of the MEMS resonator can increase by up to 150% or decrease by up to 21%, depending on the excitation approaches. This implies the necessity of a standardized testing methodology for nonlinear MEMS resonators for given end applications.

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“…It is difficult to find a rigorous definition of the adaptive decomposition algorithm; however, we think that such a type of method can form a series of sparse representations in the decomposition process, which is different with “rigid” methods, such as the Fourier or wavelets transforms, corresponding to the use of some basis (or frame) designed independently of the processed signal [ 1 , 2 ]. As many kinds of signals in engineering problems are non-linear and non-stationary, such as fault signals of mechanical equipment [ 3 , 4 , 5 , 6 , 7 , 8 ], some modal test signals [ 9 ], acoustic signals of non-destructive testing [ 10 , 11 ] and condition monitoring signals for rail track [ 12 , 13 , 14 ], the adaptive decomposition algorithm has superiority for analyzing these signals, because of decomposition flexibility.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their Applications

Liu

Luo

Huang

et al. 2018

Sensors

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The adaptive decomposition algorithm is a powerful tool for signal analysis, because it can decompose signals into several narrow-band components, which is advantageous to quantitatively evaluate signal characteristics. In this paper, we present a comparative study of four kinds of adaptive decomposition algorithms, including some algorithms deriving from empirical mode decomposition (EMD), empirical wavelet transform (EWT), variational mode decomposition (VMD) and Vold–Kalman filter order tracking (VKF_OT). Their principles, advantages and disadvantages, and improvements and applications to signal analyses in dynamic analysis of mechanical system and machinery fault diagnosis are showed. Examples are provided to illustrate important influence performance factors and improvements of these algorithms. Finally, we summarize applicable scopes, inapplicable scopes and some further works of these methods in respect of precise filters and rough filters. It is hoped that the paper can provide a valuable reference for application and improvement of these methods in signal processing.

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Nonlinearity measurement for low-pressure encapsulated MEMS gyroscopes by transient response

Cited by 13 publications

References 21 publications

A Compensation Method for Nonlinear Vibration of Silicon-Micro Resonant Sensor

A Compensation Method for Nonlinear Vibration of Silicon-Micro Resonant Sensor

Control of Spring Softening and Hardening in the Squared Daisy

A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their Applications

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