Detecting machine chatter using audio data and machine learning

被引：10

作者：

Kvinevskiy, Ilarion ^{[1
]}

Bedi, Sanjeev ^{[1
]}

Mann, Stephen ^{[2
]}

机构：

[1] Univ Waterloo, Dept Mech & Mech Engn, 200 Univ Ave W, Waterloo, ON N2L 3G1, Canada

[2] Univ Waterloo, Cheriton Sch Comp Sci, 200 Univ Ave W, Waterloo, ON N2L 3G1, Canada

来源：

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2020年 / 108卷 / 11-12期

基金：

加拿大自然科学与工程研究理事会;

关键词：

CNC machining; Chatter; Machine learning;

D O I：

10.1007/s00170-020-05571-9

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a method for detecting chatter in CNC machining. Our method uses machining learning to train a classifier to determine the chatter threshold, and we use an autoencoder to reduce the dimensionality of the data. We test our method on machining audio data, and successfully detect chatter in the validation data. Our method is amenable to use on the shop floor, as a machinist using our method needs only to classify audio as chatter and non-chatter.

引用

页码：3707 / 3716

页数：10

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