HEURISTIC FEATURE SELECTION FOR SHAVING TOOL WEAR CLASSIFICATION

被引：0

作者：

Wang, Yong ^{[1
]}

Brzezinski, Adam J. ^{[2
]}

Qiao, Xianli ^{[3
]}

Ni, Jun ^{[3
]}

机构：

[1] SUNY Binghamton, Dept Syst Sci & Ind Engn, 4400 Vestal Pkwy E, Binghamton, NY 13902 USA

[2] HGST Inc, Western Digital, 3403 Yerba Buena Rd, San Jose, CA 95135 USA

[3] Univ Michigan, Dept Mech Engn, 1255 HH Dow,2350 Hayward St, Ann Arbor, MI 48109 USA

来源：

PROCEEDINGS OF THE ASME 11TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2016, VOL 2 | 2016年

关键词：

Shaving process; condition monitoring; feature selection; tabu search; probabilistic neural network; CUTTER;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In this paper, we develop and apply feature extraction and selection techniques to classify tool wear in the shaving process. Because shaving tool condition monitoring is not well-studied, we extract both traditional and novel features from accelerometer signals collected from the shaving machine. We then apply a heuristic feature selection technique to identify key features and classify the tool condition. Run-to-life data from a shop-floor application is used to validate the proposed technique.

引用

页数：7

共 50 条

[1] Heuristic Feature Selection for Shaving Tool Wear Classification
Wang, Yong
Brzezinski, Adam J.
Qiao, Xianli
Ni, Jun
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 2017, 139 (04):
[2] A heuristic for feature selection for the classification with neural nets
Feldbusch, F
JOINT 9TH IFSA WORLD CONGRESS AND 20TH NAFIPS INTERNATIONAL CONFERENCE, PROCEEDINGS, VOLS. 1-5, 2001, : 173 - 178
[3] Feature Selection by Using Heuristic Methods for Text Classification
Sel, Ilhami
Yeroglu, Celalettin
Hanbay, Davut
2019 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND DATA PROCESSING (IDAP 2019), 2019,
[4] Feature selection for predicting tool wear of machine tools
Cheng, Wen-Nan
Cheng, Chih-Chun
Lei, Yao-Hsuan
Tsai, Ping-Chun
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2020, 111 (5-6): : 1483 - 1501
[5] Feature selection for predicting tool wear of machine tools
Wen-Nan Cheng
Chih-Chun Cheng
Yao-Hsuan Lei
Ping-Chun Tsai
The International Journal of Advanced Manufacturing Technology, 2020, 111 : 1483 - 1501
[6] Exploration of Heuristic-Based Feature Selection on Classification Problems
Qi, Qi
Li, Ni
Li, Weimin
PARALLEL ARCHITECTURE, ALGORITHM AND PROGRAMMING, PAAP 2017, 2017, 729 : 95 - 107
[7] Application of Heuristic Feature Selection in EEG based Sleep Stages Classification
Vaezi, Mahtab
Nasri, Mehdi
2020 6TH IRANIAN CONFERENCE ON SIGNAL PROCESSING AND INTELLIGENT SYSTEMS (ICSPIS), 2020,
[8] A modified multi objective heuristic for effective feature selection in text classification
Thiyagarajan, D.
Shanthi, N.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 : 10625 - 10635
[9] Machining Feature Classification and Description for Intelligent Tool Selection
Ma, Honglong
Liu, Zhanqiang
Ye, Hongtao
ADVANCES IN MACHINING AND MANUFACTURING TECHNOLOGY XII, 2014, 589-590 : 643 - +
[10] Feature selection for tool wear diagnosis using soft computing techniques
Goebel, Kai
Yan, Weizhong
American Society of Mechanical Engineers, Manufacturing Engineering Division, MED, 2000, 11 : 157 - 163

← 1 2 3 4 5 →