A Multiagent based Vehicle Engine Fault Diagnosis

Xiaobing Wu, Dharmendra Sharma

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

Abstract

A special two-level neural network Multiagent system is used in vehicle engine fault diagnosis. Each agent contains a neural network (NN) for its intelligent. The first level is used to acquire the reasons of the fault and the second level is used to classify the fault. There are a few advantages for using two-level NN multiagent system. When new knowledge of faults is acquired, only the first level needs to be retrained. An agent system is added into the second level of the whole system, and the main structure of the network need not be changed. Under the cooperation of the relative agent system, we can diagnose out complex faults and synthetic faults with less resource and better performance
Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems, KES 2007
EditorsB Apollini, R Hewlett, L Jain
Place of PublicationGermany
PublisherSpringer
Pages541-546
Number of pages6
ISBN (Print)9783540748267
Publication statusPublished - 2007
EventKES 2007 - Vietri sul Mare, Italy
Duration: 12 Sept 200714 Sept 2007

Conference

ConferenceKES 2007
Country/TerritoryItaly
CityVietri sul Mare
Period12/09/0714/09/07

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