Real time monitoring of tool breakage in a milling operation using a digital signal processor

被引:20
作者
Baek, DK
Ko, TJ
Kim, HS
机构
[1] Andong Inst Informat Technol, Kyungbuk 760830, South Korea
[2] Yeungnam Univ, Sch Mech Engn, Kyongsan 712749, South Korea
关键词
milling operation; tool breakage; real time; AR modeling; DSP (digital signal processor);
D O I
10.1016/S0924-0136(99)00493-8
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A monitoring system that can detect tool breakage and chipping in real time was developed using a digital signal. processor (DSP) board in a face milling operation. An autoregressive (AR) model and a band energy method were used to extract the features of tool states from cutting force signals. Then, two artificial neural networks, which have a parallel processing capability, were embedded on the DSP board to discriminate different malfunction states from features obtained by each of the two methods of signal processing. In experiments, we found that feature parameters extracted by AR modeling were more accurate indicators of malfunctions in die process than those from the band energy method, although the computing speed is slower. By using the selected features, we were able to monitor malfunctions in real time. (C) 2000 Elsevier Science S.A. All rights reserved.
引用
收藏
页码:266 / 272
页数:7
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