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Fault diagnosis model based on multi-manifold learning and PSO-SVM for machinery
Beijing Information Science & Technology University, Beijing, China.
Beijing Information Science & Technology University, Beijing, China.
Halmstad University, School of Business, Engineering and Science, Mechanical Engineering and Industrial Design (MTEK), Functional Surfaces.ORCID iD: 0000-0001-8058-1252
2014 (English)In: Chinese Journal of Scientific Instrument, ISSN 0254-3087, Vol. 35, no 12, 210-214 p., 210Article in journal (Refereed) Published
Abstract [en]

Fault diagnosis technology plays an important role in the industries due to the emergency fault of a machine could bring the heavy lost for the people and the company. A fault diagnosis model based on multi-manifold learning and particle swarm optimization support vector machine(PSO-SVM) is studied. This fault diagnosis model is used for a rolling bearing experimental of three kinds faults. The results are verified that this model based on multi-manifold learning and PSO-SVM is good at the fault sensitive features acquisition with effective accuracy.

Place, publisher, year, edition, pages
Beijing: Yiqi Yibiao Xuebao Zazhishe , 2014. Vol. 35, no 12, 210-214 p., 210
Keyword [en]
fault diagnosis, multi manifold learning, particle swarm optimization, support vector machine
National Category
Engineering and Technology Mechanical Engineering Reliability and Maintenance
Identifiers
URN: urn:nbn:se:hh:diva-30121ScopusID: 2-s2.0-84937426276OAI: oai:DiVA.org:hh-30121DiVA: diva2:890028
Note

Funding: Beijing Natural Science Foundation (KZ201211232039); National Natural Science Foundation of China (51275052); Funding Project for Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipalipality (PHR201106132)

Available from: 2015-12-30 Created: 2015-12-30 Last updated: 2016-01-04Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf