Predictive monitoring and failure prevention of vehicle electronic components and sensor systems

Haitao Liao, Jay Lee

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

Vehicle electronics and sensor systems have become indispensable parts in providing safety, comfort, personal communication mobility and many other advanced functions in today's vehicles. As a result, reliability requirements for these critical parts have become extremely important. To meet these requirements, more advanced technologies and tools for degradation monitoring and failure prevention are needed. Currently, the development of diagnostics and prognostics techniques, which employ accurate degradation quantification by appropriate sensor selection, location decision, and feature selection and feature fusion, still remains a vital and unsolved issue. This paper addresses several realistic concerns of failure prevention in vehicle electronics and sensor systems. A unified monitoring and prognostics approach that prevents failures by analyzing degradation features, driven by physics-of-failure, is suggested as a general framework to overcome the unsolved challenge. Many technologies and tools that could be included in this framework are presented and compared. Several examples are also provided to demonstrate these technologies and tools in practical use.

Original languageEnglish (US)
JournalSAE Technical Papers
DOIs
StatePublished - Jan 1 2006
Event2006 SAE World Congress - Detroit, MI, United States
Duration: Apr 3 2006Apr 6 2006

Fingerprint

Degradation
Monitoring
Sensors
Electronic equipment
Cellular telephone systems
Feature extraction
Fusion reactions
Physics

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering
  • Automotive Engineering

Cite this

Predictive monitoring and failure prevention of vehicle electronic components and sensor systems. / Liao, Haitao; Lee, Jay.

In: SAE Technical Papers, 01.01.2006.

Research output: Contribution to journalConference article

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