• DocumentCode
    1390807
  • Title

    Induction machine condition monitoring with higher order spectra

  • Author

    Arthur, Neil ; Penman, Jim

  • Author_Institution
    Dev. Eng. Int. Ltd., Aberdeen, UK
  • Volume
    47
  • Issue
    5
  • fYear
    2000
  • fDate
    10/1/2000 12:00:00 AM
  • Firstpage
    1031
  • Lastpage
    1041
  • Abstract
    This paper describes a novel method of detecting and unambiguously diagnosing the type and magnitude of three induction machine fault conditions from the single sensor measurement of the radial electromagnetic machine vibration. The detection mechanism is based on the hypothesis that the induction machine can be considered as a simple system, and that the action of the fault conditions are to alter the output of the system in a characteristic and predictable fashion. Further, the change in output and fault condition can be correlated allowing explicit fault identification. Using this technique, there is no requirement for a priori data describing machine fault conditions, the method is equally applicable to both sinusoidally and inverter-fed induction machines and is generally invariant of both the induction machine load and speed. The detection mechanisms are rigorously examined theoretically and experimentally, and it is shown that a robust and reliable induction machine condition-monitoring system has been produced. Further, this technique is developed into a software-based automated commercially applicable system
  • Keywords
    computerised monitoring; condition monitoring; electric machine analysis computing; fault diagnosis; induction motors; invertors; spectral analysis; a priori data; fault conditions detection; fault conditions diagnosis; fault identification; higher order spectra; induction machine condition monitoring; inverter-fed induction machines; radial electromagnetic machine vibration; sensor measurement; sinusoidally-fed induction machines; software-based automated system; Condition monitoring; Electromagnetic induction; Electromagnetic measurements; Fault detection; Fault diagnosis; Induction machines; Reliability theory; Robustness; Sensor phenomena and characterization; Vibration measurement;
  • fLanguage
    English
  • Journal_Title
    Industrial Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0046
  • Type

    jour

  • DOI
    10.1109/41.873211
  • Filename
    873211