Real-time system risk assessment using asynchronous multivariate condition monitoring data

Jian Sun, Dan Zhang, Haitao Liao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To perform real-time risk assessment for a multi-component system like the steam turbine in a nuclear power plant, the risk of the system must be predicted by taking into account multiple degradation processes and the relevant condition monitoring data. In many situations, multivariate condition monitoring data are collected asynchronously due to different sampling rates and/or variable condition monitoring schemes used in sensor networks. This raises a challenging problem in probabilistic risk assessment for such complex systems. In this paper, a Functional Principal Component Analysis (FPCA) method is developed to overcome this challenge. This method enables the prediction of remaining useful life of each component in the system and the prediction of real-time system risk based on multivariate asynchronous condition monitoring data. A numerical example is provided to demonstrate the application of the proposed method.

Original languageEnglish (US)
Title of host publication10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010
Pages1827-1838
Number of pages12
Volume3
StatePublished - 2010
Externally publishedYes
Event10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010 - Seattle, WA, United States
Duration: Jun 7 2010Jun 11 2010

Other

Other10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010
CountryUnited States
CitySeattle, WA
Period6/7/106/11/10

Fingerprint

Condition monitoring
Real time systems
Risk assessment
Steam turbines
Principal component analysis
Nuclear power plants
Sensor networks
Large scale systems
Sampling
Degradation

Keywords

  • Asynchronous degradation data
  • Functional principal component analysis
  • Remaining useful life

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality

Cite this

Sun, J., Zhang, D., & Liao, H. (2010). Real-time system risk assessment using asynchronous multivariate condition monitoring data. In 10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010 (Vol. 3, pp. 1827-1838)

Real-time system risk assessment using asynchronous multivariate condition monitoring data. / Sun, Jian; Zhang, Dan; Liao, Haitao.

10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010. Vol. 3 2010. p. 1827-1838.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sun, J, Zhang, D & Liao, H 2010, Real-time system risk assessment using asynchronous multivariate condition monitoring data. in 10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010. vol. 3, pp. 1827-1838, 10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010, Seattle, WA, United States, 6/7/10.
Sun J, Zhang D, Liao H. Real-time system risk assessment using asynchronous multivariate condition monitoring data. In 10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010. Vol. 3. 2010. p. 1827-1838
Sun, Jian ; Zhang, Dan ; Liao, Haitao. / Real-time system risk assessment using asynchronous multivariate condition monitoring data. 10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010. Vol. 3 2010. pp. 1827-1838
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