Application of Multisensor Information Fusion Technology in the Measurement of Dynamic Machining Errors of Computer Numerical Control (CNC) Machine Tools

A CNC machine tool is process control equipment integrating machine, electricity, and liquid, which makes its fault diagnosis complex and special due to its own advanced, complex, and intelligent characteristics. Traditional diagnostic methods rely on the engineering experience of technical personne...

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Autores principales:	Xiaoping Li, Yonghong Deng, Xuezhe Li
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Technology (General) T1-995
Acceso en línea:	https://doaj.org/article/88bf55648ef841818303d002ac0b614a
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spelling	oai:doaj.org-article:88bf55648ef841818303d002ac0b614a2021-11-08T02:36:11ZApplication of Multisensor Information Fusion Technology in the Measurement of Dynamic Machining Errors of Computer Numerical Control (CNC) Machine Tools1687-726810.1155/2021/6918496https://doaj.org/article/88bf55648ef841818303d002ac0b614a2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/6918496https://doaj.org/toc/1687-7268A CNC machine tool is process control equipment integrating machine, electricity, and liquid, which makes its fault diagnosis complex and special due to its own advanced, complex, and intelligent characteristics. Traditional diagnostic methods rely on the engineering experience of technical personnel, which incorporates human subjective factors, and can only perform qualitative analysis, resulting in low diagnostic efficiency. And through a single sensor to detect and diagnose the machine tool, the accuracy and credibility of the decision are low, and the system is also weak against interference. In this paper, we first summarize the composition and working principle of CNC machine tools and analyze the working condition signals generated by CNC machine tools and the sensors that collect the signals and decide to use a multisensor multisignal fusion-based approach to monitor the machine tool status. It is possible to obtain more effective and valuable information from the observed information through multiple sensors so that the goal of fusion can be achieved. In this paper, a multisensor fusion technique based on wavelet transform and neural network fusion is applied to a machine tool condition monitoring system. The theoretical basis of wavelet analysis and neural network is introduced, and the composition of the condition monitoring system and the process of applying multisensor fusion technology based on wavelet analysis and neural network in the condition monitoring system are given. A complete software and hardware system for online monitoring of CNC machine tools is established. In order to improve the accuracy of the mathematical model, the use of a neural network to fit the nonlinear data and the use of coarse set theory to simplify the relevant data can effectively solve the accurate establishment of the mathematical model in the error compensation method. The thermal error compensation method for CNC machine tools is proposed based on rough set theory, ant colony algorithm, and neural network. This paper first investigates the current development of error compensation technology for CNC machining centers, analyzes the various error sources of CNC machine tools, and finds out the influencing factors affecting the errors of CNC machine tools.Xiaoping LiYonghong DengXuezhe LiHindawi LimitedarticleTechnology (General)T1-995ENJournal of Sensors, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology (General) T1-995
spellingShingle	Technology (General) T1-995 Xiaoping Li Yonghong Deng Xuezhe Li Application of Multisensor Information Fusion Technology in the Measurement of Dynamic Machining Errors of Computer Numerical Control (CNC) Machine Tools
description	A CNC machine tool is process control equipment integrating machine, electricity, and liquid, which makes its fault diagnosis complex and special due to its own advanced, complex, and intelligent characteristics. Traditional diagnostic methods rely on the engineering experience of technical personnel, which incorporates human subjective factors, and can only perform qualitative analysis, resulting in low diagnostic efficiency. And through a single sensor to detect and diagnose the machine tool, the accuracy and credibility of the decision are low, and the system is also weak against interference. In this paper, we first summarize the composition and working principle of CNC machine tools and analyze the working condition signals generated by CNC machine tools and the sensors that collect the signals and decide to use a multisensor multisignal fusion-based approach to monitor the machine tool status. It is possible to obtain more effective and valuable information from the observed information through multiple sensors so that the goal of fusion can be achieved. In this paper, a multisensor fusion technique based on wavelet transform and neural network fusion is applied to a machine tool condition monitoring system. The theoretical basis of wavelet analysis and neural network is introduced, and the composition of the condition monitoring system and the process of applying multisensor fusion technology based on wavelet analysis and neural network in the condition monitoring system are given. A complete software and hardware system for online monitoring of CNC machine tools is established. In order to improve the accuracy of the mathematical model, the use of a neural network to fit the nonlinear data and the use of coarse set theory to simplify the relevant data can effectively solve the accurate establishment of the mathematical model in the error compensation method. The thermal error compensation method for CNC machine tools is proposed based on rough set theory, ant colony algorithm, and neural network. This paper first investigates the current development of error compensation technology for CNC machining centers, analyzes the various error sources of CNC machine tools, and finds out the influencing factors affecting the errors of CNC machine tools.
format	article
author	Xiaoping Li Yonghong Deng Xuezhe Li
author_facet	Xiaoping Li Yonghong Deng Xuezhe Li
author_sort	Xiaoping Li
title	Application of Multisensor Information Fusion Technology in the Measurement of Dynamic Machining Errors of Computer Numerical Control (CNC) Machine Tools
title_short	Application of Multisensor Information Fusion Technology in the Measurement of Dynamic Machining Errors of Computer Numerical Control (CNC) Machine Tools
title_full	Application of Multisensor Information Fusion Technology in the Measurement of Dynamic Machining Errors of Computer Numerical Control (CNC) Machine Tools
title_fullStr	Application of Multisensor Information Fusion Technology in the Measurement of Dynamic Machining Errors of Computer Numerical Control (CNC) Machine Tools
title_full_unstemmed	Application of Multisensor Information Fusion Technology in the Measurement of Dynamic Machining Errors of Computer Numerical Control (CNC) Machine Tools
title_sort	application of multisensor information fusion technology in the measurement of dynamic machining errors of computer numerical control (cnc) machine tools
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/88bf55648ef841818303d002ac0b614a
work_keys_str_mv	AT xiaopingli applicationofmultisensorinformationfusiontechnologyinthemeasurementofdynamicmachiningerrorsofcomputernumericalcontrolcncmachinetools AT yonghongdeng applicationofmultisensorinformationfusiontechnologyinthemeasurementofdynamicmachiningerrorsofcomputernumericalcontrolcncmachinetools AT xuezheli applicationofmultisensorinformationfusiontechnologyinthemeasurementofdynamicmachiningerrorsofcomputernumericalcontrolcncmachinetools
_version_	1718443112235270144

Application of Multisensor Information Fusion Technology in the Measurement of Dynamic Machining Errors of Computer Numerical Control (CNC) Machine Tools

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