Weak chatter detection in milling based on sparse dictionary

Chenxi Wang; Xingwu Zhang; Xuefeng Chen; Ruqiang Yan; Peng Wang

doi:10.1016/j.promfg.2020.05.121

Weak chatter detection in milling based on sparse dictionary

Chenxi Wang, Xingwu Zhang, Xuefeng Chen, Ruqiang Yan, Peng Wang

Research output: Contribution to journal › Conference article › peer-review

5 Scopus citations

Abstract

As one of the most unfavorable factors in milling, chatter will lead to poor surface quality, low production efficiency and tool life reduction. Chatter detection, especially weak chatter detection, is an effective way to ensure stable cutting. In this work, the milling dynamic responses based weak chatter detection method is put forward using sparse dictionary. Based on the milling dynamic equations, chatter frequencies are calculated and verified, which are the bases for chatter detection. With the calculated chatter frequencies, the sparse dictionary matrix can be constructed and the orthogonal matching pursuit (OMP) algorithm is adopted for chatter frequencies reconstruction. The proposed method can extract weak chatter frequencies accurately. Experimental results shows that the proposed method can be successful in weak chatter identification.

Original language	English
Pages (from-to)	839-843
Number of pages	5
Journal	48th SME North American Manufacturing Research Conference, NAMRC 48
Volume	48
DOIs	https://doi.org/10.1016/j.promfg.2020.05.121
State	Published - 2020
Event	48th SME North American Manufacturing Research Conference, NAMRC 48 - Cincinnati, United States Duration: Jun 22 2020 → Jun 26 2020

Bibliographical note

Funding Information:
This work is supported by National Natural Science Foundation of China (Nos. 51775408 & 51805406)，and the National Science and Technology Major Project（2017-Ⅰ-0006-0007）.

Funding Information:
This work is supported by National Natural Science Foundation of China (Nos. 51775408 & 51805406)?and the National Science and Technology Major Project?2017-?-0006-0007?.

Publisher Copyright:
© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Keywords

Milling
OMP algorithm
Sparse dictionary
Weak chatter identification

ASJC Scopus subject areas

Artificial Intelligence
Industrial and Manufacturing Engineering

Access to Document

10.1016/j.promfg.2020.05.121

Cite this

@article{d0300142a59442cb8d384228e79ccae6,

title = "Weak chatter detection in milling based on sparse dictionary",

abstract = "As one of the most unfavorable factors in milling, chatter will lead to poor surface quality, low production efficiency and tool life reduction. Chatter detection, especially weak chatter detection, is an effective way to ensure stable cutting. In this work, the milling dynamic responses based weak chatter detection method is put forward using sparse dictionary. Based on the milling dynamic equations, chatter frequencies are calculated and verified, which are the bases for chatter detection. With the calculated chatter frequencies, the sparse dictionary matrix can be constructed and the orthogonal matching pursuit (OMP) algorithm is adopted for chatter frequencies reconstruction. The proposed method can extract weak chatter frequencies accurately. Experimental results shows that the proposed method can be successful in weak chatter identification.",

keywords = "Milling, OMP algorithm, Sparse dictionary, Weak chatter identification",

author = "Chenxi Wang and Xingwu Zhang and Xuefeng Chen and Ruqiang Yan and Peng Wang",

note = "Funding Information: This work is supported by National Natural Science Foundation of China (Nos. 51775408 & 51805406)，and the National Science and Technology Major Project（2017-Ⅰ-0006-0007）. Funding Information: This work is supported by National Natural Science Foundation of China (Nos. 51775408 & 51805406)?and the National Science and Technology Major Project?2017-?-0006-0007?. Publisher Copyright: {\textcopyright} 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/); 48th SME North American Manufacturing Research Conference, NAMRC 48 ; Conference date: 22-06-2020 Through 26-06-2020",

year = "2020",

doi = "10.1016/j.promfg.2020.05.121",

language = "English",

volume = "48",

pages = "839--843",

}

TY - JOUR

T1 - Weak chatter detection in milling based on sparse dictionary

AU - Wang, Chenxi

AU - Zhang, Xingwu

AU - Chen, Xuefeng

AU - Yan, Ruqiang

AU - Wang, Peng

N1 - Funding Information: This work is supported by National Natural Science Foundation of China (Nos. 51775408 & 51805406)，and the National Science and Technology Major Project（2017-Ⅰ-0006-0007）. Funding Information: This work is supported by National Natural Science Foundation of China (Nos. 51775408 & 51805406)?and the National Science and Technology Major Project?2017-?-0006-0007?. Publisher Copyright: © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

PY - 2020

Y1 - 2020

N2 - As one of the most unfavorable factors in milling, chatter will lead to poor surface quality, low production efficiency and tool life reduction. Chatter detection, especially weak chatter detection, is an effective way to ensure stable cutting. In this work, the milling dynamic responses based weak chatter detection method is put forward using sparse dictionary. Based on the milling dynamic equations, chatter frequencies are calculated and verified, which are the bases for chatter detection. With the calculated chatter frequencies, the sparse dictionary matrix can be constructed and the orthogonal matching pursuit (OMP) algorithm is adopted for chatter frequencies reconstruction. The proposed method can extract weak chatter frequencies accurately. Experimental results shows that the proposed method can be successful in weak chatter identification.

AB - As one of the most unfavorable factors in milling, chatter will lead to poor surface quality, low production efficiency and tool life reduction. Chatter detection, especially weak chatter detection, is an effective way to ensure stable cutting. In this work, the milling dynamic responses based weak chatter detection method is put forward using sparse dictionary. Based on the milling dynamic equations, chatter frequencies are calculated and verified, which are the bases for chatter detection. With the calculated chatter frequencies, the sparse dictionary matrix can be constructed and the orthogonal matching pursuit (OMP) algorithm is adopted for chatter frequencies reconstruction. The proposed method can extract weak chatter frequencies accurately. Experimental results shows that the proposed method can be successful in weak chatter identification.

KW - Milling

KW - OMP algorithm

KW - Sparse dictionary

KW - Weak chatter identification

UR - http://www.scopus.com/inward/record.url?scp=85095136231&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85095136231&partnerID=8YFLogxK

U2 - 10.1016/j.promfg.2020.05.121

DO - 10.1016/j.promfg.2020.05.121

M3 - Conference article

AN - SCOPUS:85095136231

VL - 48

SP - 839

EP - 843

JO - 48th SME North American Manufacturing Research Conference, NAMRC 48

JF - 48th SME North American Manufacturing Research Conference, NAMRC 48

T2 - 48th SME North American Manufacturing Research Conference, NAMRC 48

Y2 - 22 June 2020 through 26 June 2020

ER -

Weak chatter detection in milling based on sparse dictionary

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this