Abstract
Sensor selection is critical for designing effective online monitoring systems for safety–critical applications. This paper proposes a novel sensor selection framework that utilizes qualitative system models to evaluate various sensor configurations based on multiple criteria. The criteria assess capabilities like fault diagnostics, risk reduction, observability, functionality, integrability, and cost. The framework uses the Integrated System Failure Analysis to generate signal features from qualitative system models. These features are used to evaluate sensor configurations against the selection criteria. The criteria can be applied as constraints or objectives for optimization. The Non-dominated Sorting Genetic Algorithm handles the multi-objective optimization to find Pareto optimal sensor deployment solutions. The framework is demonstrated on a reactor cavity cooling system case study, generating optimal configurations considering temperature, flow, pressure, density, and radiation sensors. The framework aids online monitoring system design by recommending sensor deployment configurations that balance critical capabilities. Qualitative models provide effective analysis despite the lack of operational data. The flexible criteria and multi-objective optimization enable extensive exploration of configurations in early development stages.
| Original language | English |
|---|---|
| Article number | 103228 |
| Journal | Advanced Engineering Informatics |
| Volume | 65 |
| DOIs | |
| State | Published - May 2025 |
| Externally published | Yes |
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.
Keywords
- Fault detection and discrimination
- Multiple objective optimization
- Qualitative modelling
- Safety critical system
- Sensor selection