Embedded fault diagnosis and prognosis

Julio Viola, Jose Restrepo, Ronald Harley

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The increasing use of power electronics in industry applications, energy conversion, electric vehicles (EVs), aircrafts, vessels, etc. propels efforts at early detection of potential abnormalities, which can degrade system performance, in order to reduce profit losses and even risk to human lives. In the onset of the power electronics digital control era, microprocessors were used exclusively for control tasks, mainly due to the lack in computing power needed by diagnosis algorithms. Nowadays, powerful low-cost microprocessors have become standard options for the design engineer, and embedded routines that perform real-time fault diagnosis are easily added to the design. This chapter gathers the most relevant embedded techniques for real-time condition monitoring (CM) and fault diagnosis in power drives based systems that have been reported recent years, with special emphasis on those methods using electric variables (i.e., voltage and current) as health indicators of the involved devices.

Original languageEnglish
Title of host publicationFault Diagnosis for Robust Inverter Power Drives
PublisherInstitution of Engineering and Technology
Pages103-139
Number of pages37
ISBN (Electronic)9781785614101
DOIs
StatePublished - 1 Jan 2018

Bibliographical note

Publisher Copyright:
© The Institution of Engineering and Technology 2019.

Keywords

  • Abnormalities detection
  • Aircrafts
  • Electric variables
  • Electric vehicles
  • Embedded fault diagnosis
  • Embedded fault prognosis
  • Embedded systems
  • Embedded techniques
  • Energy conversion
  • Fault diagnosis
  • Industry applications
  • Low-cost microprocessors
  • Microprocessor chips
  • Microprocessors and microcomputers
  • Power drives based systems
  • Power electronics
  • Power electronics digital control era
  • Power electronics, supply and supervisory circuits
  • Real-time condition monitoring
  • System performance degradation
  • Vessels

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