Refine your search:     
Report No.
 - 
Search Results: Records 1-20 displayed on this page of 27

Presentation/Publication Type

Initialising ...

Refine

Journal/Book Title

Initialising ...

Meeting title

Initialising ...

First Author

Initialising ...

Keyword

Initialising ...

Language

Initialising ...

Publication Year

Initialising ...

Held year of conference

Initialising ...

Save select records

JAEA Reports

A Study of reactor monitoring method with neural network

Nabeshima, Kunihiko

JAERI 1342, 119 Pages, 2001/03

JAERI-1342.pdf:7.52MB

no abstracts in English

Journal Articles

Radiation control monitor and data processing on HTTR

Nomura, Toshibumi

Hoken Butsuri, 35(1), p.127 - 135, 2000/03

no abstracts in English

Journal Articles

Plant monitoring with the combination of recurrent neural network and real-time expert system

Nabeshima, Kunihiko; Suzudo, Tomoaki; Takizawa, Hiroshi*; Ono, Tomio*; Kudo, Kazuhiko*

Proceedings of International Topical Meeting on Nuclear Plant Instrumentation, Controls, and Human-Machine Interface Technologies (NPIC&HMIT 2000) (CD-ROM), 9 Pages, 2000/00

no abstracts in English

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.

Journal Articles

Nuclear power plant monitoring with recurrent neural network

Nabeshima, Kunihiko; Suzuki, Katsuo; Inoue, K.*; *

Engineering Benefits from Neural Networks, p.257 - 260, 1998/00

no abstracts in English

JAEA Reports

A Study of reactor diagnosis method with neural network using PWR plant simulator

Nabeshima, Kunihiko; Nose, Shoichi*; *; Suzuki, Katsuo

JAERI-Research 96-051, 46 Pages, 1996/10

JAERI-Research-96-051.pdf:1.51MB

no abstracts in English

JAEA Reports

None

*; Yoshikawa, Shinji*; *; *

PNC-TY1602 95-001, 80 Pages, 1996/04

PNC-TY1602-95-001.pdf:6.42MB

no abstracts in English

JAEA Reports

Nuclear power plant monitoring method by neural network and its application to actual nuclear reactor

Nabeshima, Kunihiko; Suzuki, Katsuo; Shinohara, Yoshikuni*; E.Tuerkcan*

JAERI-Research 95-076, 33 Pages, 1995/11

JAERI-Research-95-076.pdf:1.03MB

no abstracts in English

Journal Articles

Reactor diagnosis with adaptively trained neural network

Nabeshima, Kunihiko

Tokei Suri Kenkyujo Kyodo Kenkyu Ripoto 68, 0, p.43 - 52, 1995/03

no abstracts in English

Journal Articles

On-line nuclear power plant monitoring with neural network

Nabeshima, Kunihiko; Suzuki, Katsuo; E.Tuerkcan*; Oe.Ciftcioglu*

The 3rd JSME/ASME Joint Int. Conf. on Nuclear Engineering, Vol. 3, 0, p.1551 - 1556, 1995/00

no abstracts in English

JAEA Reports

None

PNC-TN1410 94-052, 181 Pages, 1994/06

PNC-TN1410-94-052.pdf:5.58MB

no abstracts in English

Journal Articles

Centralized radiation monitoring system for the JRR-3M

;

Hoken Butsuri, 27, p.41 - 47, 1992/00

no abstracts in English

Journal Articles

JAEA Reports

Preliminary experiment of boiling detection in the reactor vessel by acoustic method

*; ; ; ; Fukami, Akihiro*; *; Igawa, Kenichi*

PNC-TN9410 91-175, 52 Pages, 1991/05

PNC-TN9410-91-175.pdf:0.75MB

An acoustic detection method is one of the FBR reactor core malfunction detection methods, and is regarded as being promising. In this study, the preliminary experiment of boiling detection by acoustic method was conducted at JOYO to measure the acoustic signal level and to investigate the applicability of the acoustic method. The experiment was performed on June 13 and 14, 1990 during the 8th periodic inspection of JOYO. The results obtained though the experiment are as follows: (1)Sodium bubbling (boiling) induced by the electric heater was detected as the fluctuation of temperature single of the thermocouple attached to surface of the electric heater. (2)Bubbling single of the acoustic detector could not be identified cleary because of the high background noise caused by the primary main pump vibration, sodium flow in the reacter vessel and the electric supply in the containment vessel. (3)The correlation between the signal of the acoustic detector or the fluctuation of temperature signal of the thermocouple and the flow rate of the primary loops was not ascertained. It became clear through this study that the validity of the reactor core malfunction detction by acoustic method depend on the peculiar noise level in the reactor vessel, and the reduction of noise is the subject for a future study.

JAEA Reports

Development of accident diagnosis and prediction system for research reactor; A Pilot system of early fault detection expert system to reduce scram frequency

Yokobayashi, Masao; Matsumoto, Kiyoshi; Murayama, Yoji; Kaminaga, Masanori; Kosaka, Atsuo

JAERI-M 90-207, 26 Pages, 1990/11

JAERI-M-90-207.pdf:0.58MB

no abstracts in English

JAEA Reports

Reactor accident diagnostic expert system DISKET

; Yokobayashi, Masao

JAERI-M 89-184, 157 Pages, 1989/11

JAERI-M-89-184.pdf:2.86MB

no abstracts in English

Journal Articles

Statistical method application to knowledge base building for reactor accident diagnostic system

; Yokobayashi, Masao; Matsumoto, Kiyoshi; Kosaka, Atsuo

Journal of Nuclear Science and Technology, 26(11), p.1002 - 1012, 1989/11

no abstracts in English

Journal Articles

A Simulation of steam generator tube rupture accident by safety analysis code RELAP5/Mod1

*; *; *; Fujiki, Kazuo; Kosaka, Atsuo; *

Tech. Rep. Inst. At. Energy,Kyoto Univ., 211, p.1 - 57, 1989/05

no abstracts in English

27 (Records 1-20 displayed on this page)