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JAEA Reports

Devdopment of an intellectual maintenance management system; Development of trouble detection and troubleshooting evaluation system

; ; Yoshikawa, Shinji

PNC-TN9410 98-023, 29 Pages, 1998/03

PNC-TN9410-98-023.pdf:1.33MB

Many research activities are conducted to enhance cost performance and safety of nuclear power plants operation and maintenance. Concept of autonomous operating system to equal the role of operators and of maintenance personnel with artificial intelligence and autonomous robots has been developed. An intellectual maintenance management system has been developed to be equipped with decision making functions of maintenance personnel. The intellectual maintenance management system is in charge of maintenance function of an autonomous plant, which consists of plant-wide monitoring, evaluation of component integrity, and scheduling of maintenance activities. In other words, this system should be equipped with preventive maintenance and corrective maintenance functions those are currently loaded on personnel. In this report, we discussed condition monitoring maintenance in the preventive maintenance. We also reported a sensor validation system development for machinery condition monitoring and diagnosis. We adopted distributed and cooperative system construction technique, which is expected recently in applications to large-scale plants. This system has inter-agent communication function for signal transmission and reception among distributed physics models of machineries. The system has been constructed for water / steam system of the LMFBR power plant. The system has been validated to be capable of cooperative sensor validation by the distributed set of agents, with quantitative indication of sensor deviation based on a newly developed fuzzy algorithm with inter-agent cooperation. The derived reference parameter value from the inter-agent evaluations also stands for the alternative measurment to the malfunctioned sensor.

JAEA Reports

Nuclear instrumentation and radiation measurement technology in the experimental fast reactor "JOYO"

Aoyama, Takafumi;

PNC-TN9420 96-058, 27 Pages, 1996/10

PNC-TN9420-96-058.pdf:1.11MB

This report introduces the nuclear instrumentation system and the major radiation measurement techniques used in the Experimental Fast Reactor "JOYO". In the introduction of the nuclear instrumentation system, system function and role as reactor plant equipment, specifications and characteristics of neutron detectors, and layout of the system are described. Reactor dosimetry was used to evaluate neutron dose and their spectra for various irradiation tests and surveilance tests performed in JOYO. The multiple-foil activation method which is currently used and the Helium Accumulation fluence Monitor (HAFM) under development are described. The fuel failure detection (FFD) and the failed fuel detection and location (FFDL) systems in which radiation measurement plays a key role are introduced. It was shown some of the major experimental results obtained from a series of fuel failure simulation tests performed in JOYO. Finally, as a new radiation measurement technique, the Plastic Scintillation Fiber (PSF) is described which is a position sensitive radiation detector that can detect the radiation dose rate at the relevant position in the fiber. The PSF is used to upgrade the gamma-ray distribution measurement to accurately evaluate the Corrosion Products (CPs) behavior in the JOYO primary coolant system.

JAEA Reports

Study on large scale knowledge base with real time operation for autonomous nuclear power plant(1); Basic concept and expecting performanse

; ; Yoshikawa, Shinji; Ozawa, kenji

PNC-TN9410 96-101, 40 Pages, 1996/04

PNC-TN9410-96-101.pdf:1.73MB

Since it is desired to enhance availability and safety of nuclear power plants operation and maintenance by removing human factor, there are many researches and developments for intelligent operation or diagnosis using artificial intelligennce (AI) technique. We have been developing an autonomous operation and maintenance system for nuclear power plants by substituting AI's and intelligent robots. It is indispensable to use various and large scale knowledge relative to plant design, operation, and maintenance, that is, whole life cycle data of the plant for the autonomous nuclear power plant. These knowledge must be given to AI system or intelligent robots adequately and opportunely. Moreover, it is necessaly to insure real time operation using the large scale knowledge base for plant control and diagnosis performance. We have been studying on the large scale and real time knowledge base system for autonomous plant. In the report, we would like to present the basic concept and expecting performance of the knowledge base for autonomous plant, especialy, autonomous control and diagnosis system.

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