Fault Detection Method of CNC Machine Tool Based on Wavelet Transform

被引：0
|
作者：
Liu, Junying [1 ]
机构：
[1] Heyuan Polytech, Coll Mech & Elect Engn, Heyuan, Guangdong, Peoples R China
来源：
PARALLEL PROCESSING LETTERS | 2022年 / 32卷 / 01N02期
关键词：
Wavelet transform; numerical control machine; operation failure; convolution calculation;
D O I：
10.1142/S0129626421410012
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In order to overcome the problems of low detection accuracy and long detection time of traditional fault detection methods for CNC machine tools, a new fault detection method for CNC machine tools based on wavelet transform is proposed in this paper. In order to improve the effectiveness of running fault detection of CNC machine tools, a wavelet transform method is used to extract the features of the running fault signals of CNC machine tools. According to the feature extraction results, the convolution calculation of the continuous wavelet transform is used to complete the fault detection of CNC machine tool according to the scale result of fault signal. The experimental results show that, compared with traditional fault detection methods, the detection accuracy and efficiency of this method is significantly better: the highest detection accuracy is 97%, and the lowest detection time is only 1.1s.
引用
收藏
页数：15
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