DocumentCode :
1945095
Title :
Immune Systems Inspired Approach to Anomaly Detection and Fault Diagnosis for Engines
Author :
Djurdjanovic, Dragan ; Liu, Jianbo ; Marko, Kenneth A. ; Ni, Jun
Author_Institution :
Univ. of Michigan, Ann Arbor
fYear :
2007
fDate :
12-17 Aug. 2007
Firstpage :
1375
Lastpage :
1382
Abstract :
As more electronic devices are integrated into automobiles to improve the reliability, drivability and maintainability, automotive diagnosis becomes increasingly difficult to deal with. Unavoidable design defects, quality variations in the production process as well as different usage patterns make it is infeasible to foresee all possible faults that may occur to the vehicle. As a result, many systems rely on limited diagnostic coverage provided by a diagnostic strategy which tests only for a priori known or anticipated failures, and presumes the system is operating normally if the full set of tests is passed. To circumvent these difficulties and provide a more complete coverage for detection of any fault, a new paradigm for design of automotive diagnostic systems is needed. An approach inspired by the functionalities and characteristics of natural immune system is presented and discussed in the paper. The feasibility of the newly proposed paradigm is also partially demonstrated through application examples.
Keywords :
automotive components; automotive electronics; fault diagnosis; internal combustion engines; anomaly detection; automobiles; automotive diagnosis; diagnostic strategy; engines; fault diagnosis; immune systems inspired approach; Automobiles; Automotive engineering; Engines; Fault detection; Fault diagnosis; Immune system; Maintenance; Production; System testing; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
ISSN :
1098-7576
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2007.4371159
Filename :
4371159
Link To Document :
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