Abstract
Robust online monitoring (OLM) technologies are expected to enable the extension or elimination of periodic sensor calibration intervals in operating and new reactors. Advances in OLM technologies will improve the safety and reliability of current and planned nuclear power systems through improved accuracy and increased reliability of sensors used to monitor key parameters. In this paper, we discuss an overview of research being performed within the Nuclear Energy Enabling Technologies (NEET)/Advanced Sensors and Instrumentation (ASI) program, for the development of OLM algorithms to use sensor outputs and, in combination with other available information, 1) determine whether one or more sensors are out of calibration or failing and 2) replace a failing sensor with reliable, accurate sensor outputs. A Gaussian Process (GP)-based uncertainty quantification (UQ) method previously developed for UQ in OLM, was adapted for this purpose. The resulting models are being evaluated for use in high-confidence signal validation for the purpose of detecting and diagnosing sensor faults, and for computing virtual sensor outputs that may be used as a temporary replacement for failing sensors. In addition to assessing sensor drift, approaches for extracting sensor response time in an automated fashion were developed, for monitoring changes in sensor response time in pressure transmitters. Such changes are also indicative of various fault modes. These algorithms were evaluated with existing measurement data from several laboratory-scale flow loops. Ongoing research in this project is focused on further evaluation of the algorithms, optimization for accuracy and computational efficiency, and integration into a suite of tools for robust OLM that are applicable to monitoring sensor calibration state in nuclear power plants.
| Original language | English |
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| Title of host publication | 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017 |
| Publisher | American Nuclear Society |
| Pages | 1176-1184 |
| Number of pages | 9 |
| ISBN (Electronic) | 9781510851160 |
| State | Published - 2017 |
| Externally published | Yes |
| Event | 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017 - San Francisco, United States Duration: Jun 11 2017 → Jun 15 2017 |
Publication series
| Name | 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017 |
|---|---|
| Volume | 2 |
Conference
| Conference | 10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017 |
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| Country/Territory | United States |
| City | San Francisco |
| Period | 06/11/17 → 06/15/17 |
Funding
The work described in this report was sponsored by the Advanced Sensors and Instrumentation (ASI) technical area within the Nuclear Energy Enabling Technologies (NEET) R&D program of the U.S. Department of Energy Office of Nuclear Energy.
Keywords
- Fault detection
- Online monitoring
- Sensor response time
- Uncertainty quantification
- Virtual sensors