Incipient multiple fault diagnosis in real time with applications to large-scale systems

Journal Article · Mon Aug 01 00:00:00 EDT 1994 · IEEE Transactions on Nuclear Science (Institute of Electrical and Electronics Engineers); (United States)

DOI:https://doi.org/10.1109/23.322777· OSTI ID:6894827

Chung, H Y; Bien, Z; Park, J H; Seon, P H ^[1]

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1. Korea Advanced Inst. of Science and Technology, Taejon (Korea, Republic of). Dept. of Electrical Engineering

By using a modified signed directed graph (SDG) together with the distributed artificial neutral networks and a knowledge-based system, a method of incipient multi-fault diagnosis is presented for large-scale physical systems with complex pipes and instrumentations such as valves, actuators, sensors, and controllers. The proposed method is designed so as to (1) make a real-time incipient fault diagnosis possible for large-scale systems, (2) perform the fault diagnosis not only in the steady-state case but also in the transient case as well by using a concept of fault propagation time, which is newly adopted in the SDG model, (3) provide with highly reliable diagnosis results and explanation capability of faults diagnosed as in an expert system, and (4) diagnose the pipe damage such as leaking, break, or throttling. This method is applied for diagnosis of a pressurizer in the Kori Nuclear Power Plant (NPP) unit 2 in Korea under a transient condition, and its result is reported to show satisfactory performance of the method for the incipient multi-fault diagnosis of such a large-scale system in a real-time manner.

• OSTI ID: 6894827
• Journal Information: IEEE Transactions on Nuclear Science (Institute of Electrical and Electronics Engineers); (United States), Vol. 41:4Pt2; ISSN 0018-9499
• Country of Publication: United States
• Language: English

Related Subjects

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REACTOR MONITORING SYSTEMS
NEURAL NETWORKS
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REACTOR INSTRUMENTATION
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