Application of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter

Cantilever structure, which needs high-frequency rotating motion, is widely used in the field of chip manufacturing. The motion stability of high-frequency rotation motion of cantilever structure directly affects the production efficiency. The traditional dynamic analysis method is no longer applica...

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Autores principales:	Xuchu Jiang, Hu Zhang, Ying Li, Biao Zhang
Formato:	article
Lenguaje:	EN
Publicado:	JVE International 2021
Materias:	high-frequency rotational motion modal analysis strain response symbolic regression dynamic adaptive technology main vibration frequency Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/90d6b6a1c7b54610950f81e030b2184c
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id	oai:doaj.org-article:90d6b6a1c7b54610950f81e030b2184c
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spelling	oai:doaj.org-article:90d6b6a1c7b54610950f81e030b2184c2021-11-15T19:20:56ZApplication of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter1392-87162538-846010.21595/jve.2021.21783https://doaj.org/article/90d6b6a1c7b54610950f81e030b2184c2021-09-01T00:00:00Zhttps://www.jvejournals.com/article/21783https://doaj.org/toc/1392-8716https://doaj.org/toc/2538-8460Cantilever structure, which needs high-frequency rotating motion, is widely used in the field of chip manufacturing. The motion stability of high-frequency rotation motion of cantilever structure directly affects the production efficiency. The traditional dynamic analysis method is no longer applicable to analyze the vibration of cantilever structure under high-frequency rotating motion. It is also urgent to control the high-frequency rotation motion of cantilever mechanism. In this paper, experiments are designed to collect strain signals of chip sorter’s cantilever under high-frequency operation, and modal parameters are extracted from time domain signals by symbolic regression algorithm. The results of modal parameter identification at high-frequency are selected as the samples, and the Gaussian process regression model of machine learning algorithm is used to train the samples. The prediction results can be used as the basis of structural stability research and vibration suppression.Xuchu JiangHu ZhangYing LiBiao ZhangJVE Internationalarticlehigh-frequency rotational motionmodal analysisstrain responsesymbolic regressiondynamic adaptive technologymain vibration frequencyMechanical engineering and machineryTJ1-1570ENJournal of Vibroengineering, Vol 23, Iss 7, Pp 1652-1662 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	high-frequency rotational motion modal analysis strain response symbolic regression dynamic adaptive technology main vibration frequency Mechanical engineering and machinery TJ1-1570
spellingShingle	high-frequency rotational motion modal analysis strain response symbolic regression dynamic adaptive technology main vibration frequency Mechanical engineering and machinery TJ1-1570 Xuchu Jiang Hu Zhang Ying Li Biao Zhang Application of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter
description	Cantilever structure, which needs high-frequency rotating motion, is widely used in the field of chip manufacturing. The motion stability of high-frequency rotation motion of cantilever structure directly affects the production efficiency. The traditional dynamic analysis method is no longer applicable to analyze the vibration of cantilever structure under high-frequency rotating motion. It is also urgent to control the high-frequency rotation motion of cantilever mechanism. In this paper, experiments are designed to collect strain signals of chip sorter’s cantilever under high-frequency operation, and modal parameters are extracted from time domain signals by symbolic regression algorithm. The results of modal parameter identification at high-frequency are selected as the samples, and the Gaussian process regression model of machine learning algorithm is used to train the samples. The prediction results can be used as the basis of structural stability research and vibration suppression.
format	article
author	Xuchu Jiang Hu Zhang Ying Li Biao Zhang
author_facet	Xuchu Jiang Hu Zhang Ying Li Biao Zhang
author_sort	Xuchu Jiang
title	Application of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter
title_short	Application of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter
title_full	Application of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter
title_fullStr	Application of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter
title_full_unstemmed	Application of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter
title_sort	application of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter
publisher	JVE International
publishDate	2021
url	https://doaj.org/article/90d6b6a1c7b54610950f81e030b2184c
work_keys_str_mv	AT xuchujiang applicationofdynamicadaptivetechnologybasedonsymbolicregressiontoidentifymodalparametersofchipsorter AT huzhang applicationofdynamicadaptivetechnologybasedonsymbolicregressiontoidentifymodalparametersofchipsorter AT yingli applicationofdynamicadaptivetechnologybasedonsymbolicregressiontoidentifymodalparametersofchipsorter AT biaozhang applicationofdynamicadaptivetechnologybasedonsymbolicregressiontoidentifymodalparametersofchipsorter
_version_	1718426857577119744

Application of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter

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