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dc.contributor.authorCilliers, A.C.
dc.identifier.citationCilliers, A.C. 2013. Benchmarking an expert fault detection and diagnostic system on the Three Mile Island accident event sequence. Annals of nuclear energy, 62:326-332. []en_US
dc.description.abstractEarly fault identification systems enable detecting and diagnosing early onset faults or fault causes which allow maintenance planning on the equipment showing signs of deterioration or failure. This includes valve and leaks and small cracks in steam generator tubes usually detected by means of ultrasonic inspection. We have shown (Cilliers and Mulder, 2012) that detecting faults early during transient operation in NPPs is possible when coupled with a reliable reference to compare plant measurements with during transients. We have also shown (Cilliers, 2013) that by correlating the fault detection information as received from distributed systems it is possible to diagnose the faults in terms of location and magnitude. This paper makes use of the techniques and processes developed in the previous papers and apply it to a case study of the Three Mile Island accident. In this way we can determine how the improved information available could present the operator with a better idea to the state of the plant during situations where a combination of faults and transients prevents the operator and conventional systems to recognise the abnormal behaviouren_US
dc.subjectNuclear power planten_US
dc.subjectfault detectionen_US
dc.subjectfault isolationen_US
dc.subjectfault characterisationen_US
dc.subjectplant diagnosticsen_US
dc.subjectplant simulatoren_US
dc.titleBenchmarking an expert fault detection and diagnostic system on the Three Mile Island accident event sequenceen_US
dc.contributor.researchID11858176 - Cilliers, Anthonie Christoffel

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