Passportization of refueling operations to monitor the state of equipment in the NPP core

The work is focused on increasing the relatability of nuclear power plants by monitoring the overloading of fuel cartridges carried out by the refueling machine. The necessity of developing a control system that prevents failures during reloading operations is shown. It is argued that the development of the system must be preceded by the stage of observation and systematization of the current characteristics of the object in the process of repeated operations with various overloaded products. Simplification of the monitoring procedure is achieved by using the current signals consumed by the machine drives during operation. The scheme of registration of diagnostic signals is presented. Approaches to signal processing and analysis are described. The proposed approach was tested during the refueling campaign at the Rostov NPP. Based on the current signals registered during the overload process, the possibility of creating passports of overloading operations has been demonstrated. For the purpose of clustering, the principal component method is applied to the current parameters. The developed passports can be used as reference pattern for subsequent overload monitoring. It is shown that the signals corresponding to the main hoist drive can be used to control the efforts of the refueling machine when removing fuel. Thus, the paper substantiates the prospects of the control system for the reloading process based on the registration and analysis of the current consumed by the drives of the refueling machine.

1. Portnoj YU.T. Sistemy upravleniya peregruzochnymi mashinami AES s reaktorami VVER-1000. Moskva: Trudy NPP VNIIEM. 2001:225-234. (in Russian).

2. Steele J. A., Martin L. A., McArthur S. D. J., Moyes A., Mc-Donald J. R., Howie D., Elrick R., Yule I. Y. An intelligent system for interpreting the nuclear refuelling process within an AGR. Proceedings of the Institution of Mechanical Engineers, Part A. 2003;159-167.

3. Lapkis A.A., Nikiforov V.N., Pervushin L.A. Vibroacoustical Certification of Operating Modes of WWER Fuel-Handling Machines. Global nuclear safety. 2018;2(27):82-90. (in Russian).

4. DIN ISO 10816-6-2015. Mechanical Vibration. Assessment of the Machine Condition Based on the Results of Vibration Measurements on Non-Rotating Parts. Part 6. Machines with Reciprocating Motion with a Rated Power over 100 kW. (in Russian).

5. Riera-Guasp M., Antonino-Daviu J. A., and Capolino G.-A. Advances in electrical machine, power electronic and drive condition monitoring and fault detection: State of the art. IEEE Transactions on Electron Devices. 2015;62(3):1746-1759.

6. Choi S., Pazouki E., Baek J., and Bahrami H. R. Iterative condition monitoring and fault diagnosis scheme of electric motor for harsh industrial application. IEEE Transactions on Electron Devices. 2015;62(3):1760-1769.

7. Abidova Е.А., Chernov A.V., Khegai L.S. Improvement of Information Processing Methods in NPP Equipment Diagnostics Systems. Monograph. Moscow. Volgodonsk Institute of Engineering and Technology - branch of the Federal State Autonomous Educational Institution of Higher Education "National Research Nuclear University" MEPhI». 2019. ISBN 978-5-7262-2589-0. (in Russian).

8. Dylevsky A.V., Vlasova O.O., Rakitin D.A. Construction of transients in systems with distributed parameters. Bulletin of the Voronezh state University. Ser. System analysis and information technologies. 2016;(3):85-89.

9. Al Bugharbee H., Trendafilova I.A. Methodology for fault detection in rolling element bear-ings using singular spectrum analysis. International Conference on Engineering Vibration 2017 (ICoEV 2017) – 4-7 September 2017, Sofia, Bulgaria. 2018:1-5. Available from: https://strathprints.strath.ac.uk/62663.

10. Markov D.V. Osnovnye zakonomernosti izmeneniya svojstv i harakteristik topliva VVER i RBMK novogo pokoleniya v period ekspluatacii po rezul'tatam kompleksnyh poslereaktornyh issledovanij. Doctor of Technical Sciences thesis. Moscow. National Research Center "Kurchatov Institute". 2018 (in Russian)