Signal singularity detection based on the hermitian wavelet for fault diagnosis

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

Abstract

On Big Data analysis for fault diagnosis, health monitoring & fault tolerance of rockets and spacecrafts in aerospace industry, as the local anomaly induced signals tend to have singularity, this paper presents a guideline to employ the time-scale amplitude and phase diagrams based on the Hermitian wavelet transform to identify signal singularities. Firstly, the principle of signal singularity detection based on wavelet transform is formulated. Secondly, the definitions, characteristics, and expressions of the Hermitian wavelet transform is studied. Finally, simulations are carried out to verify the proposed algorithms.

Original languageEnglish
Title of host publicationProceedings - 2014 International Conference on Cloud Computing and Big Data, CCBD 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages116-118
Number of pages3
ISBN (Electronic)9781479966219
DOIs
StatePublished - 17 Mar 2014
Event2014 International Conference on Cloud Computing and Big Data, CCBD 2014 - Wuhan, China
Duration: 12 Nov 201414 Nov 2014

Publication series

NameProceedings - 2014 International Conference on Cloud Computing and Big Data, CCBD 2014

Conference

Conference2014 International Conference on Cloud Computing and Big Data, CCBD 2014
Country/TerritoryChina
CityWuhan
Period12/11/1414/11/14

Keywords

  • amplitude diagram
  • hermitian wavelet
  • phase diagram
  • signal singularity
  • time-scale analysis

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