Adaptive On-Line Monitoring for Improved Equipment Reliability

75797-This project supports the Nuclear Energy Plant Optimization Program objective to ensure the continued safe and reliable operation of the Nation¿s nuclear power plants. To achieve this goal, it is essential that accurate on-line information about the current state of the equipment be available to the operators. Such information is needed to determine the operability of safety and control systems, the condition of active equipment, the necessity of preventative maintenance, and the status of sensory systems. This project will demonstrate new adaptive on-line learning algorithms to enable the automated optimization of equipment-condition-monitoring software for a wide variety of power plant systems. These artificial intelligence techniques will be used to ensure the accurate measurement of key reactor and plant parameters, assess equipment in-service performance, and determine equipment integrity and the need for maintenance. In Phase I, the new algorithms will be incorporated into a proven three-step diagnostic framework consisting of a parameter estimation step, a fault detection step, and a diagnostic decision step. Commercial Applications and Other Benefits as described by the awardee: In addition to the application for nuclear power plants, the on-line equipment-condition-monitoring software should be applicable to any process control system where unexpected process interruptions could cause equipment failures, false alarms, or unsafe conditions. The new capability should substantially improve plant uptime, thereby increasing output and operating revenue in a wide range of industries.