Model-based intelligent fault detection and diagnosis for mating electric connectors in robotic wiring harness assembly systems

Jian Huang, Toshio Fukuda, Takayuki Matsuno

Research output: Contribution to journalArticle

44 Citations (Scopus)

Abstract

Mating a pair of electric connectors is one of the most important steps in a robotic wiring harness assembly system. A class of piecewise linear force models is proposed to describe both the successful and the faulty mating processes of connectors via an elaborate analysis of forces during different phases. The corresponding parameter estimation method of this model is also presented by adapting regular least-square estimation methods. A hierarchical fuzzy pattern matching multidensity classifier is proposed to realize fault detection and diagnosis for the mating process. This classifier shows good performance in diagnosis. A typical type of connectors is investigated in this paper. The results can easily be extended to other types. The effectiveness of proposed methods is finally confirmed through experiments.

Original languageEnglish
Pages (from-to)86-94
Number of pages9
JournalIEEE/ASME Transactions on Mechatronics
Volume13
Issue number1
DOIs
Publication statusPublished - Feb 2008
Externally publishedYes

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Keywords

  • Fault detection and diagnosis
  • Fuzzy pattern matching
  • Modeling
  • Robotic wiring harness assembly

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

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