0

Full Content is available to subscribers

Subscribe/Learn More  >

Fault Detection and Identification in NPP Instruments Using Kernel Principal Component Analysis

[+] Author Affiliations
Jianping Ma

University of Western Ontario, London, ON, Canada

Jin Jiang

University of Western Ontario, London, ON, Canada; Xi’an Jiaotong University, Xi’an, Shaanxi, China

Paper No. ICONE18-29777, pp. 765-771; 7 pages
doi:10.1115/ICONE18-29777
From:
  • 18th International Conference on Nuclear Engineering
  • 18th International Conference on Nuclear Engineering: Volume 1
  • Xi’an, China, May 17–21, 2010
  • Conference Sponsors: Nuclear Engineering Division
  • ISBN: 978-0-7918-4929-3
  • Copyright © 2010 by ASME

abstract

In this paper, kernel principal component analysis (KPCA) is studied for fault detection and identification in the instruments of nuclear power plants. We propose to use mean values of the sensor reconstruction errors of a KPCA model for fault isolation and identification. They provide useful information about the directions and magnitudes of detected faults, which are usually not available from other fault isolation techniques. The performance of the method is demonstrated by applications to real NPP measurements.

Copyright © 2010 by ASME

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In