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Micromachines 2018, 9(5), 246; https://doi.org/10.3390/mi9050246

Improved Morphological Filter Based on Variational Mode Decomposition for MEMS Gyroscope De-Noising

1,2
,
1,3,* , 1,3,* and 1,3
1
National Key Laboratory of Electronic Measurement Technology, North University of China, Shanxi 030051, China
2
College of Mechatronics Engineering, North University of China, Shanxi 030051, China
3
School of Instrument and Electronics, North University of China, Shanxi 030051, China
*
Authors to whom correspondence should be addressed.
Received: 19 April 2018 / Revised: 13 May 2018 / Accepted: 15 May 2018 / Published: 17 May 2018
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Abstract

An adaptive multi-scale method based on the combination generalized morphological filter (CGMF) is presented for de-noising of the output signal from a MEMS gyroscope. A variational mode decomposition is employed to decompose the original signal into multi-scale modes. After choosing a length selection for the structure element (SE), the adaptive multi-scale CGMF method reduces the noise corresponding to the different modes, after which a reconstruction of the de-noised signal is obtained. From an analysis of the effect of de-noising, the main advantages of the present method are that it: (i) effectively overcomes deficiencies arising from data deviation compared with conventional morphological filters (MFs); (ii) effectively targets the different components of noise and provides efficacy in de-noising, not only primarily eliminating noise but also smoothing the waveform; and (iii) solves the problem of SE-length selection for a MF and produces feasible formulae of indicators such as the power spectral entropy and root mean square error for mode evaluations. Compared with the other current signal processing methods, the method proposed owns a simpler construction with a reasonable complexity, and it can offer better noise suppression effect. Experiments demonstrate the applicability and feasibility of the de-noising algorithm. View Full-Text
Keywords: MEMS gyroscope; variational mode decomposition; morphological filter; denoising algorithm MEMS gyroscope; variational mode decomposition; morphological filter; denoising algorithm
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Wu, Y.; Shen, C.; Cao, H.; Che, X. Improved Morphological Filter Based on Variational Mode Decomposition for MEMS Gyroscope De-Noising. Micromachines 2018, 9, 246.

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