A parallel distributed knowledge-based system for turbine generator fault diagnosis

Real-time fault diagnosis for turbine generators is a fairly complex problem. Parallel processing and distributed artificial intelligence (DAI), as rapidly emerging and promising technologies, provide powerful tools for solving this difficult problem. Based on the study of the basic fault diagnosis process for turbine generators, the idea of parallel 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 turbine 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.