Nuclear Power Plant Monitoring Method by Neural Network and its Application to Actual Nuclear Reactor

NTIS Section

demand in very efficient manner. A new conceptual model of power maneuverability has been proposed for the design of the limitation system and for its validation. The limitation function consists of the feedback control algorithm through the turbine load and the feed-forward algorithm directly through the control system. Also, the limitation system monitors overall operation processes throughout a nuclear power plant. It interacts with most of major systems by implementing communication networks with effective layered architecture. Numerous kinds of data, either input to limitation system or output from limitation system, differ in reliability criteria, required sampling rate, accuracy, delay, and so on. And then, for the design and evaluation of the limitation systeni, a comprehensive and efficient computer simulation scheme has been established for nuclear operations. Based on the conceptual design in software of the 1 st year results, the detailed design of the limitation system is to be performed during the 2 nd year for the implementation into the hardware of a stand-alone digital system. The products of the project could be directly applicable to the followingnuclear unit adopting the limitation system, providing the bumpless transition to the commercial design phase. summarized. (author). 26 refs., 34 figs., 11 tabs. Descriptors: *Nuclear Power Plants; *Reactor Operation; Automation; Control Systems; Digital Systems; Expert Systems; Knowledge Base; Limiting Values; Nuclear Liability; Reactor Control Systems; Reactor Instrumentation Identifiers: *Foreign Technology; EDB/220400; NTISDEE Section Headings: 77H (Nuclear Science and TechnologyReactor Engineering and Nuclear Power Plants) Toward An Implementation of Hierarchical Hybrid Control Systems for the Integrated Operation of Industrial Complexes Hennet, J. C.; Chacon, E.; Moreno, W. Centre National de la Recherche Scientifique, Toulouse (France). Lab. d’Automatique et d’Analyse des Systemes. Corp. Source Codes: 044050004; 9100200 Report No.: CNRS-LAAS-96014 Jan 96 8p Language: English Journal Announcement: GRA19623; ERA9644 U.S. Sales Only. NTIS Prices: PC A02/MF A01 Country of Publication: France This paper proposes a software/hardware architecture to achieve the implementation of a global control strategy for continuous production industrial complexes. The industrial complex is described by a set of continuous process units, coordinated hierarchically by Discrete Event Dynamic Systems (DEDS) parametrized by human decisions. The concept presented in this paper uses a hierarchical structure in three levels. The first level, the Direct Control Level (DCL), is implemented as a Hybrid System. The second level, the Decision Level (DL), performs the coordination and optimization tasks to define the set of operating points to control the Continuous Process Units under a defined control strategy. The third level, the Planning Level (PL), is the uppermost level where the overall control strategy is defined taking into account internal and external factors. In addition, this paper shows the computational support (hardware, software, and networking) which is necessary to implement the proposed

VII

integrated scheme. (authors). 14 refs., 6 figs. Descriptors: *Computerized Control Systems; *Hydroelectric power plants; *Petroleum plants; Automation; Computer Architecture; Computer Networks; Data Acquisition Systems; Data Base Management; Decision Tree Analysis; Expert Systems; Hybrid Computers; Implementation; ManMachine Systems; Optimization; Petroleum Industry; Real Time Systems; System Failure Analysis; Task Scheduling Identifiers: *Foreign Technology; EDB1990200; EDB/ 130100; EDB/020300; NTISDEE Section Headings: 99B (Chemistry-Industrial Chemistry and Chemical Process Engineering); 41B (Manufacturing Technology-Computer Aided Manufacturing (CAM)); 971 (Energy-Electric Power Production); 97K (Energy-Fuels)

Nuclear Power Plant Monitoring Method by Neural Network and its Application to Actual Nuclear Reactor Naheshima, K.; Suzuki, K.; Shinohara, Y.; Tuerkcan, E. Japan Atomic Energy Research Inst., Tokyo. Corp. Source Codes: 014802000; 3413000 Report No.: JAERI-RESEARCH-95-076 Nov 95 39p Language: Japanese Journal Announcement: GRA19623; ERA9645 in Japanese NTIS Prices: PC AO4/MF A01 Country of Publication: Japan In this paper, the anomaly detection method for nuclear power plant monitoring and its program are described by using a neural network approach, which is based on the deviation between measured signals and output signals of neural network model. The neural network used in this study has three layered auto-associative network with 12 input/ output, and backpropagation algorithm is adopted for learning. Furthermore, to obtain better dynamical model of the reactor plant, a new learning technique was developed in which the learning process of the present neural network is divided into initial and adaptive learning modes. The test results at the actual nuclear reactor shows that the neural network plant monitoring system is successful1 in detecting in real-time the symptom of small anomaly over a wide power range including reactor start-up, shut-down and stationary operation. (author). Descriptors: *Reactor Monitoring Systems; Algorithms; Expert Systems; Functional Models; In-Service Inspection; Learning; Manuals; Neural Networks; Nuclear Power Plants; Reactor Kinetics; Reactor Operation Identifiers: *Foreign Technology; EDB/220400; NTISDEE Section Headings: 77H (Nuclear Science and TechnologyReactor Engineering and Nuclear Power Plants)

Problemy Otsenki Ehffektivnosti Ispol’zovaniya Uskoritel’noj Ustanovki. (Problems of Estimating the Efficiency of Accelerator Using) Borovikov, A. A.; Khromova, G. N. Gosudarstvennyi Komitet po Ispol’zovaniyu Atomnoi Energii SSSR, Serpukhov. Inst. Fiziki Vysokikh Energii. Corp. Source Codes: 05 172600 1; 2852000 Report No.: IFVE-OLU-93-150 1993 8p