Application of novelty detection methods to health monitoring and typical fault diagnosis of a turbopump

Lei Hu, Niaoqing Hu, Bin Fan, Fengshou Gu

Research output: Contribution to journalConference article

3 Citations (Scopus)


Novelty detection is the identification of deviations from a training set. It is suitable for monitoring the health of mechanical systems where it usually is impossible to know every potential fault. In this paper, two novelty detectors are presented. The first detector which integrates One-Class Support Vector Machine (OCSVM) with an incremental clustering algorithm is designed for health monitoring of the turbopump, while the second one which is trained on sensor fault samples is designed to recognize faults from sensors and faults actually from the turbopump. Analysis results showed that these two detectors are both sensitive and efficient for the health monitoring of the turbopump.

Original languageEnglish
Article number012128
Number of pages11
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 28 May 2012
Event25th International Congress on Condition Monitoring and Diagnostic Engineering: Sustained Prosperity through Proactive Monitoring, Diagnosis and Management - University of Huddersfield, Huddersfield, United Kingdom
Duration: 18 Jun 201220 Jun 2012
Conference number: 25 (Link to Conference Website )


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