An intelligent sensor system approach for reliable tool flank wear recognition

An intelligent sensor system approach for reliable flank wear monitoring in turning is described. Based on acoustic emission and force sensing, an intelligent sensor system integrates multiple sensing, advanced feature extraction and information fusion methodology. Spectral, statistical and dynamic...

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Bibliographic Details
Published inInternational journal of advanced manufacturing technology Vol. 14; no. 2; pp. 77 - 84
Main Authors Niu, Y. M., Wong, Y. S., Hong, G. S.
Format Journal Article
LanguageEnglish
Published Heidelberg Springer Nature B.V 01.02.1998
Subjects
Acoustic emission
Cutting wear
Data integration
Decision making
Feature extraction
Machine shops
Multisensor fusion
Neural networks
Sensors
Tool wear
Turning (machining)
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Summary:An intelligent sensor system approach for reliable flank wear monitoring in turning is described. Based on acoustic emission and force sensing, an intelligent sensor system integrates multiple sensing, advanced feature extraction and information fusion methodology. Spectral, statistical and dynamic analysis have been used to determine primary features from the sensor signals. A secondary feature refinement is further applied to the primary features in order to obtain a more correlated feature vector for the tool flank wear process. An unsupervised ART2 neural network is used for the fusion of AE and force information and decision-making of the tool flank wear state. The experimental results confirm that the developed intelligent sensor system can be reliably used to recognise the tool flank wear state over a range of cutting conditions.
ISSN:0268-3768
1433-3015
DOI:10.1007/BF01322215