W. Xue et Sz. Yang, A PARALLEL DISTRIBUTED KNOWLEDGE-BASED SYSTEM FOR TURBINE-GENERATOR FAULT-DIAGNOSIS, Artificial intelligence in engineering, 10(4), 1996, pp. 335-341
Real-time fault diagnosis for turbine generators is a fairly complex p
roblem. Parallel processing and distributed artificial intelligence (D
AI), as rapidly emerging and promising technologies, provide powerful
tools for solving this difficult problem. Based on the study of the ba
sic fault diagnosis process for turbine generators, the idea of parall
el processing and DAI is introduced into the held of fault diagnosis.
Parallelism at four different levels in the fault diagnosis process is
proposed. It lays down the theoretical basis for the development of a
real-time parallel distributed fault diagnosing system for the turbin
e generator of a 300 MW fossil power plant. The diagnostic system can
continuously monitor the vibration of the turbine generator as well as
various process data. Copyright (C) 1996 Elsevier Science Ltd.