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Proceedings Paper

Information integration and diagnosis analysis of equipment status and production quality for machining process
Author(s): Tao Zan; Min Wang; Jianzhong Hu
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Paper Abstract

Machining status monitoring technique by multi-sensors can acquire and analyze the machining process information to implement abnormity diagnosis and fault warning. Statistical quality control technique is normally used to distinguish abnormal fluctuations from normal fluctuations through statistical method. In this paper by comparing the advantages and disadvantages of the two methods, the necessity and feasibility of integration and fusion is introduced. Then an approach that integrates multi-sensors status monitoring and statistical process control based on artificial intelligent technique, internet technique and database technique is brought forward. Based on virtual instrument technique the author developed the machining quality assurance system - MoniSysOnline, which has been used to monitoring the grinding machining process. By analyzing the quality data and AE signal information of wheel dressing process the reason of machining quality fluctuation has been obtained. The experiment result indicates that the approach is suitable for the status monitoring and analyzing of machining process.

Paper Details

Date Published: 27 May 2011
PDF: 6 pages
Proc. SPIE 7997, Fourth International Seminar on Modern Cutting and Measurement Engineering, 79973G (27 May 2011); doi: 10.1117/12.888551
Show Author Affiliations
Tao Zan, Beijing Univ. of Technology (China)
Min Wang, Beijing Univ. of Technology (China)
Jianzhong Hu, Beijing Univ. of Technology (China)


Published in SPIE Proceedings Vol. 7997:
Fourth International Seminar on Modern Cutting and Measurement Engineering
Jiezhi Xin; Lianqing Zhu; Zhongyu Wang, Editor(s)

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