By Topic

Model-Based Intelligent Fault Detection and Diagnosis for Mating Electric Connectors in Robotic Wiring Harness Assembly Systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Jian Huang ; Nagoya Univ., Nagoya ; Toshio Fukuda ; Takayuki Matsuno

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.

Published in:

IEEE/ASME Transactions on Mechatronics  (Volume:13 ,  Issue: 1 )