This report will be of interest to transit railcar maintenance professionals concerned with improving railcar maintenance fault-diagnostic capabilities through the use of artificial intelligence (AI) technologies. For the purpose of this report. AI is defined as a computer program that uses human problem-solving techniques to assist and augment the diagnostic process. Seven AI technologies--expert systems, case-based reasoning, model-based reasoning, artificial neural networks, computer vision, fuzzy logic, and knowledge-based systems-are investigated to determine their potential for application to the diagnosis of transit railcar systems and subsystems. The report concludes that AI technology is sufficiently mature for cost-effective application in the transit railcar diagnostic process and provides recommendations for implementation of the technology.
Artificial Intelligence for Transit Railcar Diagnostics
1994
72 pages
Report
Keine Angabe
Englisch
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