Automated Detection and Characterization of ESD-Induced Soft Failures Using Image- and Audio-Based Methods

Omid Hoseini Izadi, Javad Meiguni, Kenji Araki, Hideki Shumiya, David J. Pommerenke

Research output: Contribution to journalArticle

Abstract

Audio- and image-based soft failure detection methods are developed, which can detect both severe failures (such as system hang) and subtle ones (such as glitch or a momentary disturbance on display). Incorporating the developed detection methods with a robotic ESD (electrostatic discharge) tester, we developed a fully automated soft failure investigation tool. Using this fully automated tool, we obtained failure-specific susceptibility maps for a camera (our target device). These susceptibility maps not only illustrated the sensitive locations of the device, they also showed what type of soft failure is correlated with which locations.
Original languageEnglish
Article number9082875
Pages (from-to)1546-1554
Number of pages9
JournalIEEE Transactions on Electromagnetic Compatibility
Volume62
Issue number4
DOIs
Publication statusPublished - Aug 2020

Keywords

  • Electrostatic discharges
  • Image edge detection
  • Probes
  • Webcams
  • Strips
  • Robots
  • Automatization
  • detection algorithm
  • electrostatic discharge (ESD)
  • immunity test
  • signal processing
  • soft failure
  • susceptibility map

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering

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