The shape characteristic detection of tool breakage in milling operations

Detection of tool failure is very important in automated manufacturing. All previously developed tool breakage detection approaches in milling operations have adopted the strategy of parameter detection in which the detection of tool breakage was carried out according to values of specific parameter...

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Veröffentlicht in:International journal of machine tools & manufacture 1997-11, Vol.37 (11), p.1651-1660
Hauptverfasser: Hongjian, Xue, Kechong, Yang, Rong, Yang
Format: Artikel
Sprache:eng
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Zusammenfassung:Detection of tool failure is very important in automated manufacturing. All previously developed tool breakage detection approaches in milling operations have adopted the strategy of parameter detection in which the detection of tool breakage was carried out according to values of specific parameters selected to reflect tool state (with or without tool breakage). In this paper the new concept of shape characteristic detection of tool breakage in milling operations is proposed. The detection of tool breakage is conducted according to the shape characteristics of discrete dyadic wavelet decomposition of cutting force. By means of the proposed method, the influence caused by the variation of cutting parameters and transients is eliminated. The proposed method is conducted in two steps. In the first step, cutting force signals are decomposed by discrete dyadic wavelet, with the shape characteristic vectors then being generated by the proposed shape characteristic vector-generating algorithm. In the second step, the shape characteristic vectors are fast classified by the ART2 neural networks. The accuracy and effectiveness of the proposed method are verified by numerous experiments.
ISSN:0890-6955
1879-2170
DOI:10.1016/S0890-6955(97)00021-7