Abstract :
Technology advances in condition monitoring are employing an increasing number of on-line sensors to automatically monitor the status and performance of the complex systems required for power generation. Proper use of this information can assist in saving operating and maintenance expenses, in addition to reducing unscheduled outages and catastrophic failures. However, the large volume of available data from these sensors can overwhelm personnel and require extensive interpretation. Correctly handling this information requires expertise in machine design and operating limits, sophisticated on-line monitoring instrumentation, and alarm processing and interpretation. By using a diagnostic monitoring system, a broad base of knowledge can be brought to bear to help nonexperts investigate a particular equipment problem. The advantages of such a system include: making expertise available to general workers even when a human expert is unavailable; improving the efficiency and consistency of an expert; improving the quality of performance of nonexperts; and training less experienced personnel. Because a computer system can be interrogated as to why a particular conclusion was made, less experienced users can gain knowledge about the approach experts use to solve problems. The main components of such a diagnostic system are briefly outlined and include a database, an expert system and a user interface
Keywords :
computerised monitoring; condition monitoring; database management systems; expert systems; hydroelectric generators; power engineering computing; user interfaces; alarm processing; catastrophic failures reduction; condition monitoring; database; diagnostic monitoring system; expert system; hydro generators; machine design; maintenance expenses saving; on-line monitoring instrumentation; on-line sensors; operating expenses saving; operating limits; performance monitoring; status monitoring; training; unscheduled outages reduction; user interface; Computerized monitoring; Condition monitoring; Databases; Diagnostic expert systems; Humans; Instruments; Personnel; Power generation; Sensor systems; User interfaces;