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.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
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.