Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/28949
Title: Detection of motor bearing outer raceway defect by wavelet packet transformed motor current signature analysis
Authors: Lau, ECC
Ngan, HW
Keywords: Bearing
fault diagnosis
motor current signature analysis (MCSA)
wavelet packet transforms
Issue Date: 2010
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on instrumentation and measurement, 2010, v. 59, no. 10, 5446405, p. 2683-2690 How to cite?
Journal: IEEE transactions on instrumentation and measurement 
Abstract: Motor current signature analysis (MCSA) is a method of sampling the running current through a data logger at high sampling speed, followed by using mathematical tools such as fast Fourier transform (FFT) to identify relevant motor signature changes in the frequency spectrum for motor fault identification. Although there are numerous types of motor fault, research conducted by Electric Power Research Institute (EPRI) indicated that motor bearing fault accounted for more than 40% of all types of motor fault. The main aim of this paper is to evaluate the use of MCSA for detecting bearing outer raceway defect. Stage-by-stage experimental verification shows that the method of MCSA is effective in detecting bearing fault with the use of wavelet packet transformation (WPT). In addition, a novel linear application of linear regression for wavelet data analysis is applied and presented in this paper.
URI: http://hdl.handle.net/10397/28949
ISSN: 0018-9456
EISSN: 1557-9662
DOI: 10.1109/TIM.2010.2045927
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