Westinghouse Electric Corporation

Christian T Kemper

James C Bellows

Robert L Osborne

Simon Lowenfeld

Avelino J Gonzalez

Pamela J Kleinosky

Mark S Fox

The system of the present invention uses the importance of a piece of malfunctioning equipment, the severity and the confidence level in a diagnosis to determine repair priority of the equipment by obtaining the product (46) of the confidence level (CF), importance (IMP) and severity (SEV). The these variables are determined by expert system rules. The severity is the reciprocal (88) of the time to failure. The importance (44) is the cost to repair the maximum damage when the malfunction continues. A malfunction can affect several pieces of equipment in combination, the severity and importance associated with each piece is combined (70) with the confidence and used to determine the repair priority. When the diagnosis of a malfunction is by malfunctioning sensors, the expected equipment life (40) and the availability (86) of sensors that provide a partial backup are considered in prioritizing sensor as well as equipment repair. When a primary piece of equipment is backed up (100), the effect of both pieces of equipment failing (106) is considered in prioritizing the repair. The system ranks the repair of all possible malfunctions on a common scale. The system gives a complete repair priority picture and allows the cost effectiveness to be maximized.

Automated system to prioritize repair of plant equipment

Diagnostic apparatus utilized to monitor a steam turbine-generator power plant. A plurality of sensors around the plant provide data to the diagnostic apparatus which utilizes a digital computer to come to some conclusion relative to actual or impending malfunctions in the plant components. The computer utilizes an expert system diagnosis which establishes a plurality of subsystems which are generic and can be applied to any sensor to obtain indications of (a) sensor output movement, (b) validated sensor readings and (c) malfunction indications based on conclusions reached in (a) and (b).

Diagnostic apparatus

Sensor based diagnostic apparatus for performing on-line realtime monitoring of an industrial or other operating system. The diagnostic apparatus has a rule network for propagation of belief leading to one or more possible malfunctions of equipment in the operating system. The propagation of belief is dynamically altered as a function of the operating conditions of the sensors themselves.

Rule based diagnostic system with dynamic alteration capability

A diagnostic system wherein a central diagnostic center receives sensor data relative to the operating condition of a plurality of remote plants. Each plant records just certain sensor signals and transmits them at respective prescheduled transmisssion times. If certain activation limits are exceeded, a data link with the diagnostic center is immediately established so that the data may be transmitted ahead of its normally scheduled transmission time in order that an immediate diagnostic analysis be made on the plant. A communication link between the plant and diagnostic center is kept open for a predetermined period of time in which more data may be sent from the plant to the diagnostic center, and results and instructions, sent from the diagnostic center back to the plant. Such instructions may include the changing of certain parameters in the examination of the sensor signals.

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Winter Park, FL, United States of America

Christian T Kemper