Weighted Basis Pursuit Denoising Algorithm and Its Application in Gear Fault Diagnosis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In order to improve the fault signature extracting performance in signal processing for gearboxes' fault diagnosis, a weighted Basis Pursuit Denoising(BPD) algorithm is proposed. The algorithm introduces weighted matrix into classical BPD model which picks small threshold values for target frequencies letting them stand out in the spectrum after iteration. The algorithm is verified by both simulation signal and an actual gear fault signal from a test bench, in which the algorithm shows great performance and excellent capability of extracting signal feature of gear fault under complex interference and strong noises distraction.

Original languageEnglish
Title of host publicationICSMD 2021 - 2nd International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665427470
DOIs
StatePublished - 2021
Event2nd International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2021 - Nanjing, China
Duration: 21 Oct 202123 Oct 2021

Publication series

NameICSMD 2021 - 2nd International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence

Conference

Conference2nd International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2021
Country/TerritoryChina
CityNanjing
Period21/10/2123/10/21

Keywords

  • gear fault diagnosis
  • ISTA
  • signal processing
  • sparse representation
  • weighted Basis Pursuit Denoising

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