An application of a recursive Kalman filtering algorithm in rotating machinery fault diagnosis

Jian-Da Wu, Chin Wei Huang, Rongwen Huang

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)


In this paper, an application of adaptive order tracking fault diagnosis technique based on recursive Kalman filtering algorithm is presented. Order tracking fault diagnosis technique is one of the important tools for fault diagnosis of rotating machinery. Conventional methods of order tracking are primarily based on Fourier analysis with reference to shaft speed. In this study, a high-resolution order tracking method with adaptive Kalman filter is used to diagnose the fault in a gear set and damaged engine turbocharger wheel blades. The adaptive Kalman filtering algorithm can overcome the problems encountered in conventional methods. The problem is treated as the tracking of frequency-varying bandpass signals. Ordered amplitudes can be calculated with high resolution after experimental implementation. Experiments are also carried out to evaluate the proposed system in gear-set defect diagnosis and engine turbocharger wheel blades damaged under various conditions. The experimental results indicate that the proposed algorithm is effective in fault diagnosis of both cases.

Original languageEnglish
Pages (from-to)411-419
Number of pages9
JournalNDT and E International
Issue number5
Publication statusPublished - 2004 Jul 1

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Condensed Matter Physics
  • Mechanical Engineering

Fingerprint Dive into the research topics of 'An application of a recursive Kalman filtering algorithm in rotating machinery fault diagnosis'. Together they form a unique fingerprint.

Cite this