Journal
IEEE TRANSACTIONS ON NUCLEAR SCIENCE
Volume 65, Issue 3, Pages 856-865Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNS.2018.2803658
Keywords
Analytical redundancy; fault detection and identification (FDI); Fisher discriminant analysis (FDA); parity space algorithm; performance monitoring; real-time FDI
Funding
- NSERC
- UNENE
Ask authors/readers for more resources
A parity space approach to monitoring and fault detection and identification of systems in nuclear power plants (NPPs) can be beneficial. However, if the number of fault classes exceeds the total independent residual signatures, the parity space method needs to be further enhanced to achieve the optimal fault classification. This situation happens frequently in NPP applications, where the safety and reliability are paramount. A possible enhancement proposed in this paper is to combine Fisher discriminant analysis with the parity space method to maximize the scatter among different fault classes, while minimizing the scatter within each class. Under identical conditions, the proposed technique can achieve optimal separation among different fault classes. Design, real-time implementation, and experimental evaluation of the proposed method are detailed in this paper. The implemented system has been validated on the Nuclear Power Control Test Facility to demonstrate the feasibility. The test results have revealed many salient features of the proposed method with potential applications in NPPs.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available