Sensor signal segmentation for tool condition monitoring

Sebastian Bombiński , Krzysztof Błażejak , Mirosław Nejman , Krzysztof Jemielniak

Abstract

Robust tool condition monitoring system requires reliable, repeatable selection of representative segments of the sensor signals. In commercial TCM systems and most of laboratory ones useful signal segments are selected by the system user, which is difficult, inconvenient, prone to random changes of cutting conditions and human errors. The paper presents algorithms for fully automatic detection of actual cutting (elimination of air cutting), selection of relatively stable signal segments representative of the tool condition and elimination of the overabundance of signal data in case of long operations or tool lives.
Author Sebastian Bombiński ITW
Sebastian Bombiński,,
- The Institute of Manufacturing Processes
, Krzysztof Błażejak ITW
Krzysztof Błażejak,,
- The Institute of Manufacturing Processes
, Mirosław Nejman ITW
Mirosław Nejman,,
- The Institute of Manufacturing Processes
, Krzysztof Jemielniak ITW
Krzysztof Jemielniak,,
- The Institute of Manufacturing Processes
Pages155-160
Publication size in sheets0.5
Book Rafi Wertheim, Steffen Ihlefeldt, Carsten Hochmuth, Matthias Putz (eds.): 7th HPC 2016 – CIRP Conference on High Performance Cutting, vol. 46, 2016, Elsevier Procedia, ISBN 9781510824638, 639 p.
Keywords in Polishdiagnostyka stanu narzędzia, przetwarzanie sygnałów
Keywords in Englishtool condition monitoring, signal processing
DOIDOI:10.1016/j.procir.2016.03.203
Languageen angielski
Score (nominal)0
Citation count*0 (2016-07-08)
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