Condition monitoring (CM) is an effective way to improve the tool life of a cutting tool. However, CM techniques have not been applied to monitor tool wear in an industrial gear shaving application. Therefore, this paper introduces a novel, sensor-based, data-driven, tool wear estimation method for monitoring gear shaver tool condition. The method is applied on an industrial gear shaving machine and used to differentiate between four different tool wear conditions (new, slightly worn, significantly worn, and broken). This research focuses on combining, expanding, and implementing CM techniques in an application where no previous work has been done. In order to realize CM, this paper discusses each aspect of CM, beginning with data collection and pre-processing. Feature extraction (in the time, frequency, and time-frequency domains) is then explained. Furthermore, feature dimension reduction using principal component analysis (PCA) is described. Finally, feature fusion using a multi-layer perceptron (MLP) type of artificial neural network (ANN) is presented.
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ASME 2008 International Manufacturing Science and Engineering Conference collocated with the 3rd JSME/ASME International Conference on Materials and Processing
October 7–10, 2008
Evanston, Illinois, USA
Conference Sponsors:
- Manufacturing Engineering Division
ISBN:
978-0-7918-4852-4
PROCEEDINGS PAPER
Feature-Based Tool Condition Monitoring in a Gear Shaving Application
A. J. Brzezinski,
A. J. Brzezinski
University of Michigan, Ann Arbor, MI
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Y. Wang,
Y. Wang
Huazhong University of Science and Technology, Wuhan, China
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D. K. Choi,
D. K. Choi
Kangnung National University, Kangnung, Korea
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J. Ni
J. Ni
University of Michigan, Ann Arbor, MI
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A. J. Brzezinski
University of Michigan, Ann Arbor, MI
Y. Wang
Huazhong University of Science and Technology, Wuhan, China
D. K. Choi
Kangnung National University, Kangnung, Korea
X. Qiao
University of Michigan, Ann Arbor, MI
J. Ni
University of Michigan, Ann Arbor, MI
Paper No:
MSEC_ICM&P2008-72297, pp. 65-74; 10 pages
Published Online:
July 24, 2009
Citation
Brzezinski, AJ, Wang, Y, Choi, DK, Qiao, X, & Ni, J. "Feature-Based Tool Condition Monitoring in a Gear Shaving Application." Proceedings of the ASME 2008 International Manufacturing Science and Engineering Conference collocated with the 3rd JSME/ASME International Conference on Materials and Processing. ASME 2008 International Manufacturing Science and Engineering Conference, Volume 2. Evanston, Illinois, USA. October 7–10, 2008. pp. 65-74. ASME. https://doi.org/10.1115/MSEC_ICMP2008-72297
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