Abstract
Sensor selection is a critical task in the design of online/health monitoring and diagnosis systems and therefore essential in developing the corresponding safety-critical systems. To assist research in improving the competitiveness of advanced reactors through cost optimization and plant performance, this paper evaluates and integrates multiple sensor selection criteria for the purpose of optimizing sensor localization/placement in online monitoring. The selection strategy is aimed at supporting the design of an intelligent online monitoring. In general, the goal of the sensor selection process is to provide a suite of sensors that fulfill specified performance requirements within a set of system constraints. The identified sensor selection criteria will evaluate the critical performance of possible sensor deployments, such as the reliability, the functionality, the integrity, and the cost of sensors, the capability for fault diagnosis and prognosis. These characteristics can be obtained and evaluated using the outcomes of the integrated systems failure analysis method, which is a model-based fault analysis method used to simulate the propagation of possible failure modes of components within the system under analysis. By analyzing the outcomes of the failure analysis method, the features of the signals within the monitored system under various component failures (e.g., the coast down of pumps, the inner or outer leakage of valves, the deviation of sensors, etc.) can be extracted. These features are evaluated by the sensor selection criteria introduced in this paper to choose the optimal sensor deployment. In this paper, the effectiveness of the selection criteria is verified using a fully passive reactor cavity cooling system of a modular high temperature gas-cooled reactor. The application of the sensors selection criteria is illustrated by adopting the criteria in determining optimal sensors requirements and their placement in the case study system.
| Original language | English |
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| Title of host publication | Proceedings of 13th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, NPIC and HMIT 2023 |
| Publisher | American Nuclear Society |
| Pages | 1568-1577 |
| Number of pages | 10 |
| ISBN (Electronic) | 9780894487910 |
| DOIs | |
| State | Published - 2023 |
| Externally published | Yes |
| Event | 13th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, NPIC and HMIT 2023 - Knoxville, United States Duration: Jul 15 2023 → Jul 20 2023 |
Publication series
| Name | Proceedings of 13th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, NPIC and HMIT 2023 |
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Conference
| Conference | 13th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, NPIC and HMIT 2023 |
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| Country/Territory | United States |
| City | Knoxville |
| Period | 07/15/23 → 07/20/23 |
Funding
This work was prepared as an account of work sponsored by the U.S. Department of Energy, Office of Nuclear Energy Advanced Sensors and Instrumentation program under DOE Contract DE-NE-19-17045. Neither the U.S. Government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness, of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. References herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the U.S. Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the U.S. Government or any agency thereof. We also thank Framatome for providing information related to the RCCS in the MHTGR.
Keywords
- Non-dominated Pareto fronts
- Online monitoring system
- Sensor placement optimization
- Sensor selection criteria