A Novel High-Speed and High-Accuracy Mathematical Modeling Method of Complex MEMS Resonator Structures Based on the Multilayer Perceptron Neural Network

MEMS resonators have become core devices in a large number of fields; however, due to their complex structures, the finite element analysis (FEA) method is still the main method for their theoretical analysis. The traditional finite element analysis method faces the disadvantages of large calculatio...

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Autores principales:	Qingsong Li, Kuo Lu, Kai Wu, Hao Zhang, Xiaopeng Sun, Xuezhong Wu, Dingbang Xiao
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	mathematical modeling finite element analysis artificial neural network multilayer perceptron neural network structural optimization design Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/46f78252f0b6433798a7fc146bb058b5
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id	oai:doaj.org-article:46f78252f0b6433798a7fc146bb058b5
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spelling	oai:doaj.org-article:46f78252f0b6433798a7fc146bb058b52021-11-25T18:23:03ZA Novel High-Speed and High-Accuracy Mathematical Modeling Method of Complex MEMS Resonator Structures Based on the Multilayer Perceptron Neural Network10.3390/mi121113132072-666Xhttps://doaj.org/article/46f78252f0b6433798a7fc146bb058b52021-10-01T00:00:00Zhttps://www.mdpi.com/2072-666X/12/11/1313https://doaj.org/toc/2072-666XMEMS resonators have become core devices in a large number of fields; however, due to their complex structures, the finite element analysis (FEA) method is still the main method for their theoretical analysis. The traditional finite element analysis method faces the disadvantages of large calculation amount and long simulation time, which limits the development of high-performance MEMS resonators. This paper demonstrates a high-speed and high-accuracy simulation tool based on the artificial neural network, where a multilayer perceptron (MLP) neural network model is constructed. The typical structural parameters of MEMS resonator are used as the input layer, and its performance indicators produced by the finite element analysis method are the output layer. After iteratively trained with 4000 samples, the cumulative error of the neural network decreases to 0.0017 and a prediction network model is obtained. Compared with the finite element analysis results, the structural accuracy error predicted by the neural network model can be controlled within 6%, but its runtime is shortened by 15,000 times. This high-speed and high-accuracy mathematical modeling method can effectively improve the analyzing efficiency and provide a promising tool for the design and optimization of different complex MEMS resonators, which exhibit remarkable accuracy and speed.Qingsong LiKuo LuKai WuHao ZhangXiaopeng SunXuezhong WuDingbang XiaoMDPI AGarticlemathematical modelingfinite element analysisartificial neural networkmultilayer perceptron neural networkstructural optimization designMechanical engineering and machineryTJ1-1570ENMicromachines, Vol 12, Iss 1313, p 1313 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	mathematical modeling finite element analysis artificial neural network multilayer perceptron neural network structural optimization design Mechanical engineering and machinery TJ1-1570
spellingShingle	mathematical modeling finite element analysis artificial neural network multilayer perceptron neural network structural optimization design Mechanical engineering and machinery TJ1-1570 Qingsong Li Kuo Lu Kai Wu Hao Zhang Xiaopeng Sun Xuezhong Wu Dingbang Xiao A Novel High-Speed and High-Accuracy Mathematical Modeling Method of Complex MEMS Resonator Structures Based on the Multilayer Perceptron Neural Network
description	MEMS resonators have become core devices in a large number of fields; however, due to their complex structures, the finite element analysis (FEA) method is still the main method for their theoretical analysis. The traditional finite element analysis method faces the disadvantages of large calculation amount and long simulation time, which limits the development of high-performance MEMS resonators. This paper demonstrates a high-speed and high-accuracy simulation tool based on the artificial neural network, where a multilayer perceptron (MLP) neural network model is constructed. The typical structural parameters of MEMS resonator are used as the input layer, and its performance indicators produced by the finite element analysis method are the output layer. After iteratively trained with 4000 samples, the cumulative error of the neural network decreases to 0.0017 and a prediction network model is obtained. Compared with the finite element analysis results, the structural accuracy error predicted by the neural network model can be controlled within 6%, but its runtime is shortened by 15,000 times. This high-speed and high-accuracy mathematical modeling method can effectively improve the analyzing efficiency and provide a promising tool for the design and optimization of different complex MEMS resonators, which exhibit remarkable accuracy and speed.
format	article
author	Qingsong Li Kuo Lu Kai Wu Hao Zhang Xiaopeng Sun Xuezhong Wu Dingbang Xiao
author_facet	Qingsong Li Kuo Lu Kai Wu Hao Zhang Xiaopeng Sun Xuezhong Wu Dingbang Xiao
author_sort	Qingsong Li
title	A Novel High-Speed and High-Accuracy Mathematical Modeling Method of Complex MEMS Resonator Structures Based on the Multilayer Perceptron Neural Network
title_short	A Novel High-Speed and High-Accuracy Mathematical Modeling Method of Complex MEMS Resonator Structures Based on the Multilayer Perceptron Neural Network
title_full	A Novel High-Speed and High-Accuracy Mathematical Modeling Method of Complex MEMS Resonator Structures Based on the Multilayer Perceptron Neural Network
title_fullStr	A Novel High-Speed and High-Accuracy Mathematical Modeling Method of Complex MEMS Resonator Structures Based on the Multilayer Perceptron Neural Network
title_full_unstemmed	A Novel High-Speed and High-Accuracy Mathematical Modeling Method of Complex MEMS Resonator Structures Based on the Multilayer Perceptron Neural Network
title_sort	novel high-speed and high-accuracy mathematical modeling method of complex mems resonator structures based on the multilayer perceptron neural network
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/46f78252f0b6433798a7fc146bb058b5
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_version_	1718411253235318784

A Novel High-Speed and High-Accuracy Mathematical Modeling Method of Complex MEMS Resonator Structures Based on the Multilayer Perceptron Neural Network

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