Statistical methods for condition assessment of low-failure assets

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

For (electrical) infrastructure assets a high reliability is required. When assets cannot be monitored and no condition information is available, statistical methods can be used to assess their condition. This paper discusses statistical methods to assess the condition of LV cables, which is a typical example of electric components with a very low failure rate. Two survival methods and three classification methods are compared. The Cox Proportional Hazard model proved to be the most suitable. The influence of variables on the failure probability provides insight in failure mechanisms and asset groups which have a high failure probability. In this paper it is proved that a great amount of information can be gained using survival analysis for ageing infrastructure assets.

Original languageEnglish
Title of host publication2019 IEEE Milan PowerTech, PowerTech 2019
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)978-1-5386-4722-6
DOIs
Publication statusPublished - 1 Jun 2019
Event2019 IEEE Milan PowerTech, PowerTech 2019 - Milan, Italy
Duration: 23 Jun 201927 Jun 2019

Conference

Conference2019 IEEE Milan PowerTech, PowerTech 2019
CountryItaly
CityMilan
Period23/06/1927/06/19

Fingerprint

Statistical methods
Hazards
Cables
Aging of materials

Keywords

  • Asset management
  • Big data applications
  • Power distribution
  • Power grids
  • Regression analysis

Cite this

Klerx, M., Morren, J., & Slootweg, H. (2019). Statistical methods for condition assessment of low-failure assets. In 2019 IEEE Milan PowerTech, PowerTech 2019 [8810966] Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/PTC.2019.8810966
Klerx, Maikel ; Morren, Johan ; Slootweg, Han. / Statistical methods for condition assessment of low-failure assets. 2019 IEEE Milan PowerTech, PowerTech 2019. Piscataway : Institute of Electrical and Electronics Engineers, 2019.
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Klerx, M, Morren, J & Slootweg, H 2019, Statistical methods for condition assessment of low-failure assets. in 2019 IEEE Milan PowerTech, PowerTech 2019., 8810966, Institute of Electrical and Electronics Engineers, Piscataway, 2019 IEEE Milan PowerTech, PowerTech 2019, Milan, Italy, 23/06/19. https://doi.org/10.1109/PTC.2019.8810966

Statistical methods for condition assessment of low-failure assets. / Klerx, Maikel; Morren, Johan; Slootweg, Han.

2019 IEEE Milan PowerTech, PowerTech 2019. Piscataway : Institute of Electrical and Electronics Engineers, 2019. 8810966.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Klerx M, Morren J, Slootweg H. Statistical methods for condition assessment of low-failure assets. In 2019 IEEE Milan PowerTech, PowerTech 2019. Piscataway: Institute of Electrical and Electronics Engineers. 2019. 8810966 https://doi.org/10.1109/PTC.2019.8810966