Sensor signal segmentation for tool condition monitoring
Sebastian Bombiński , Krzysztof Błażejak , Mirosław Nejman , Krzysztof Jemielniak
AbstractRobust 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.
|Publication size in sheets||0.5|
|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 Polish||diagnostyka stanu narzędzia, przetwarzanie sygnałów|
|Keywords in English||tool condition monitoring, signal processing|
|Citation count*||0 (2016-07-08)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.