Customized Wavelet for Bearing Defect Detection-Reference-Cited by-同舟云学术

Customized Wavelet for Bearing Defect Detection

Published:2004-12-01 Issue:4 Volume:126 Page:740-745
ISSN:0022-0434
Container-title:Journal of Dynamic Systems, Measurement, and Control
language:en
Short-container-title:

Author:

Holm-Hansen Brian T.,Gao Robert X.,Zhang Li¹

Affiliation:

1. Department of Mechanical and Industrial Engineering, University of Massachusetts, Amherst, MA 01003

Abstract

This paper presents a new, structural dynamics-based wavelet transformation technique for bearing defect detection. Specifically, a customized wavelet was developed analytically, using the scaling function derived from the actual impulse response of a ball bearing. Experiments under various loading conditions have confirmed that the customized wavelet provides a better match to the defect-induced signals of the bearing than a standard wavelet commonly used in the literature and is, thus, more effective in detecting bearing structural defects.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Link

http://asmedigitalcollection.asme.org/dynamicsystems/article-pdf/126/4/740/5502136/740_1.pdf

Reference33 articles.

1. Tepfer, D., and Baldor, L., 1996, “Sikorsky Says Cause of Crash was Subcontractor’s Bearings,” Conn. Post, 5(179), pp. 11.

2. Duquette, A., 1998, “FAA to Require Improved Engine Inspections,” Press Release APA 93-98, FAA Office of Public Affairs, Washington DC.

3. Mori, K., Kasashima, N., Yoshioka, T., and Ueno, Y., 1996, “Prediction of Spalling on a Ball Bearing by Applying the Discrete Wavelet Transform to Vibration Signals,” Wear, 195(1-2), pp. 162–168.

4. Yang, J., Xiong, X., and Xiong, S., 1999, “Damage Detection of Roller Bearing Using Wavelet Transform,” Proc. of Int. Modal Analysis Conference-IMAC, Vol. 2, Society for Experimental Mechanics, Bethel, CT, pp. 1980–1983.

5. Gupta, P., 1984, Advanced Dynamics of Rolling Elements, Springer-Verlag, New York.

Cited by 27 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The Bearing Surface Defect Detection Method Combining Magnetic Particle Testing and Deep Learning;Applied Sciences;2024-02-21

2. Efficient data management for intelligent manufacturing;Manufacturing from Industry 4.0 to Industry 5.0;2024

3. Bearings in Aerospace, Application, Distress, and Life: A Review;Journal of Failure Analysis and Prevention;2023-05-31

4. The Effect of Sensor Integration on the Load Carrying Capacity of Gears;Machines;2022-10-02

5. Deep Learning-Driven Data Curation and Model Interpretation for Smart Manufacturing;Chinese Journal of Mechanical Engineering;2021-07-16