Application of a model-based fault detection system to nuclear plant signals
- Argonne National Lab., IL (United States)
- Florida Power Corp., Crystal River, FL (United States)
To assure the continued safe and reliable operation of a nuclear power station, it is essential that accurate online information on the current state of the entire system be available to the operators. Such information is needed to determine the operability of safety and control systems, the condition of active components, the necessity of preventative maintenance, and the status of sensory systems. To this end, ANL has developed a new Multivariate State Estimation Technique (MSET) which utilizes advanced pattern recognition methods to enhance sensor and component operational validation for commercial nuclear reactors. Operational data from the Crystal River-3 (CR-3) nuclear power plant are used to illustrate the high sensitivity, accuracy, and the rapid response time of MSET for annunciation of a variety of signal disturbances.
- Research Organization:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Energy Research, Washington, DC (United States)
- DOE Contract Number:
- W-31109-ENG-38
- OSTI ID:
- 481606
- Report Number(s):
- ANL/RA/CP-92110; CONF-970765-2; ON: DE97052981; TRN: 97:011072
- Resource Relation:
- Conference: International conference on intelligent systems applications to power systems, Seoul (Korea, Republic of), 6-10 Jul 1997; Other Information: PBD: [1997]
- Country of Publication:
- United States
- Language:
- English
Similar Records
Applications of pattern recognition techniques to online fault detection
Dynamics sensor validation for reusable launch vehicle propulsion.