Wavelet-based statistical health monitoring and fault diagnosis method

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

1 Scopus Citations
View graph of relations

Author(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings : 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC 2017)
PublisherIEEE
Pages334-338
ISBN (Electronic)9781509040209
ISBN (Print)9781509040216
Publication statusPublished - Aug 2017

Conference

Title2017 International Conference on Sensing, Diagnostics, Prognostics, and Control
LocationShanghai Aircraft Customer Service Co., Ltd.
PlaceChina
CityShanghai
Period16 - 18 August 2017

Abstract

In this paper, a wavelet-based statistical method is proposed for health monitoring and fault diagnosis. This method integrates the statistical process control technology and the discrete wavelet transform. A statistical indicator based on discrete wavelet transform is constructed, and the X-bar chart is used to monitor the indicator. The fault frequency can be identified in the Hilbert envelope spectrum of the signal which is reconstructed by the out-of-control levels. Thus with the proposed method, one can not only detect a process change but also identify the fault type. An experimental study is conducted to demonstrate the effectiveness of the proposed method.

Research Area(s)

  • Bearing fault, Fault diagnosis, Monitoring, SPC, Wavelet transform

Citation Format(s)

Wavelet-based statistical health monitoring and fault diagnosis method. / Fan, Wei; Zhou, Qiang.

Proceedings : 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control (SDPC 2017). IEEE, 2017. p. 334-338.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review