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In-vehicle network level fault diagnostics using fuzzy inference systems
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Suwatthikul, Jittiwut, McMurran, Ross and Jones, R. Peter (2011) In-vehicle network level fault diagnostics using fuzzy inference systems. Applied Soft Computing, Volume 11 (Number 4). pp. 3709-3719. doi:10.1016/j.asoc.2011.02.001 ISSN 1568-4946.
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Official URL: http://dx.doi.org/10.1016/j.asoc.2011.02.001
Abstract
This paper presents an application of an Adaptive-Network-based Fuzzy Inference System (ANFIS) for pre-diagnosing incipient underlying in-vehicle network problems which possibly could cause further failures. An experiment on ANFIS-based pre-diagnosis of network level faults on Controller Area Network (CAN) by utilising available network protocol signals, such as error frames, is reported. The experimental results show that the pre-diagnostic system can efficiently classify causes of error frames transmitted on a CAN bus, and identify "network health" which indicates healthiness of the network when being used for message communication. The potential causes of the faults can be narrowed down, and further network diagnostics and prognostics can be performed. (C) 2011 Elsevier B.V. All rights reserved.
Item Type: | Journal Article | ||||
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Subjects: | T Technology > TL Motor vehicles. Aeronautics. Astronautics | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||
Library of Congress Subject Headings (LCSH): | Automobiles -- Electronic equipment, Fuzzy systems, Fault location (Engineering), Automatic control, Controller Area Network (Computer network) | ||||
Journal or Publication Title: | Applied Soft Computing | ||||
Publisher: | Elsevier BV | ||||
ISSN: | 1568-4946 | ||||
Official Date: | 2011 | ||||
Dates: |
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Volume: | Volume 11 | ||||
Number: | Number 4 | ||||
Page Range: | pp. 3709-3719 | ||||
DOI: | 10.1016/j.asoc.2011.02.001 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Funder: | National Electronics and Computer Technology Centre (NECTEC), Thailand, Jaguar PLC, Land-Rover Ltd. |
Data sourced from Thomson Reuters' Web of Knowledge
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