Failure Rate Modeling Using Equipment Inspection Data

Brown, Richard E.; Frimpong, G.; Willis, H Lee

doi:10.1109/tpwrs.2004.825824

Cited by 114 publications

(44 citation statements)

References 16 publications

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“…So far, the average failure rate is allocated to all components in a population [29]. Although applying the average failure rate to all components of a population is practical, it cannot characterize the actual condition of each individual component.…”

Section: Failure Rate Modelingmentioning

confidence: 99%

“…Every component is unique and the external environment such as weather, location in the grid, usage, and maintenance influence the wear process differently. As a result, developed models might underestimate or overrate component reliability for certain time periods [29]. [30] describes the limits of a constant failure rate for system reliability models and suggests that actual failure distributions of components must be determined as accurately as possible.…”

Section: Failure Rate Modelingmentioning

confidence: 99%

Section: Failure Rate Modelingmentioning

confidence: 99%

“…Modeling the failure rate by using equipment inspection data has been presented in [29]. The method in [29] reflects component criticality in system models and allows a more precise distribution of customer reliability. Failure rate estimation as part of an integrated general asset management model for electric utilities has been presented in [31].…”

Section: Failure Rate Modelingmentioning

confidence: 99%

“…Moreover, [29] describes the challenge of determining the failure rate of the best and worst inspection outcome which is necessary for the interpolation. This determination is not required for the proposed method in this paper.…”

Section: Failure Rate Modelingmentioning

confidence: 99%

See 4 more Smart Citations

Individual failure rates for transformers within a population based on diagnostic measures

Jürgensen

Nordström

Hilber

2016

Electric Power Systems Research

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This is the published version of a paper published in Electric power systems research. Citation for the original published paper (version of record):Jürgensen, J H., Nordström, L., Hilber, P. (2016) Individual failure rates for transformers within a population based on diagnostic measures. The high monetary value of a transformer has placed the transformer life-time optimization into the focus of asset management. The average failure rate has created reasonable results within reliability modeling, however, it cannot reflect the probability of failure for an individual transformer. In this paper, a method is introduced to calculate individual failure rates for a transformer population based on failure statistics and diagnostic measurements such as dissolved gas, and 2-furfuraldehyde analysis. The method is applicable to all types of components and the comprehensibility makes it effective for practical implementation. The results are evaluated against two health indices based on a weight factor and fuzzy logic. It can be observed that the presented individual failure rates are plausible representatives of the transformer's probability of failure. Therefore, the results can also be utilized for asset management decision-making.

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Section: Failure Rate Modelingmentioning

confidence: 99%

Section: Failure Rate Modelingmentioning

confidence: 99%

Section: Failure Rate Modelingmentioning

confidence: 99%

Section: Failure Rate Modelingmentioning

confidence: 99%

Section: Failure Rate Modelingmentioning

confidence: 99%

See 3 more Smart Citations

Individual failure rates for transformers within a population based on diagnostic measures

Jürgensen

Nordström

Hilber

2016

Electric Power Systems Research

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References

2014

Risk Assessment of Power Systems

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Failure rate estimation of overhead electric distribution lines considering data deficiency and population variability

Moradkhani

Haghifam

Mohammadzadeh

2014

Int. Trans. Electr. Energ. Syst.

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Summary Estimating a precise data‐driven failure rate of electrical components in the distribution networks is a prominent task in asset management of the network. To estimate the failure rates in the overhead distribution lines, there are two main challenges: data deficiency and population variability. In order to overcome difficulties, this paper proposes an applicable method based on hierarchical Bayesian Poisson regression (HBPR). The proposed method is applied to the real distribution system with 34 feeders. The deviance information criterion and model checking procedure are used to compare the goodness of fit between HBPR and exchangeable hierarchical Bayesian model (EHBM). Finally, to show the functionality of the HBPR model, the failure rates obtained from HPBR and EHBM are used to calculate reliability indices, and the results are compared with the actual value of indices. Copyright © 2014 John Wiley & Sons, Ltd.

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Failure Rate Modeling Using Equipment Inspection Data

Cited by 114 publications

References 16 publications

Individual failure rates for transformers within a population based on diagnostic measures

Individual failure rates for transformers within a population based on diagnostic measures

References

Failure rate estimation of overhead electric distribution lines considering data deficiency and population variability

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