PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
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.
Tao Zan,Min Wang, andJianzhong Hu
"Information integration and diagnosis analysis
of equipment status and production quality for machining process", Proc. SPIE 7997, Fourth International Seminar on Modern Cutting and Measurement Engineering, 79973G (26 May 2011); https://doi.org/10.1117/12.888551
ACCESS THE FULL ARTICLE
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
The alert did not successfully save. Please try again later.
Tao Zan, Min Wang, Jianzhong Hu, "Information integration and diagnosis analysis of equipment status and production quality for machining process," Proc. SPIE 7997, Fourth International Seminar on Modern Cutting and Measurement Engineering, 79973G (26 May 2011); https://doi.org/10.1117/12.888551