Automotive fault, diagnosis - Part II: A distributed agent diagnostic system

被引：34
作者：
Murphey, YL [1 ]
Crossman, JA
Chen, ZH
Cardillo, J
机构：
[1] Univ Michigan, Dept Elect & Comp Engn, Dearborn, MI 48128 USA
[2] Ford Motor Co, Diagnost Serv Planning, Adv Diagnost Design, Allen Pk, MI 48101 USA
来源：
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | 2003年 / 52卷 / 04期
基金：
美国国家科学基金会;
关键词：
D O I：
10.1109/TVT.2003.814236
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, we describe a novel diagnostic archi- tecture, distributed diagnosis agent system (DDAS), developed for automotive fault diagnosis. The DDAS consists of a vehicle diagnostic agent and a number of signal diagnostic agents,each of which is reponsible for the fault diagnosis of one particular, signal using either a single or multiple signals depending on the complexity of signal faults. Each signal diagnostic agent is developed using common framework that involves signal segmentation, a utomatic signal feature extraction and selection, and machine learning. The signal diagnostic agents can concurrently execute their tasks; some agents possess information concerning the cause of faults for other agents, while other agents merely report symptoms. Together, these signal agents present a full picture of the behavior of the vehicle under diagnosis to the vehicle diagnostic a of diagnostics agent DDAS provides three levels decisions: signal-segment fault, signal fault, and vehicle fault. DDAS is scalable and versatile and has been implemented for fault detection of electronic control unit (ECU) signals; experiment results are presented and discussed in this paper.
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收藏
页码：1076 / 1098
页数：23
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