Failure prediction of power cables using failure history and operational conditions

Sachan, Swati; Zhou, Chengke; Bevan, Geraint; Alkali, Babakalli

doi:10.1109/icpadm.2015.7295288

Cited by 9 publications

(9 citation statements)

References 8 publications

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“…Power cable failure occurs due to random, ageing, or cumulated effect of both the causes. A random failure can occur due to degradation in a small section of a cable circuit such as poor workmanship, a manufacturing defect, or sudden mechanical (Sachan et al 2015b), whereas ageing failures occur in cable insulation due to dominant electrothermal stress in daily load cycle (Sachan et al 2015a, b). Most common mode of insulation failure is electrical breakdown of insulation, breakdown at the electrical interface, and insulation thermal breakdown (Dong et al 2014;Orton 2013).…”

Section: Length Of Maintenance Periodmentioning

confidence: 99%

“…The failure events in NHPP models are not independent and identically distributed. Thus, it considers the fact that cable is a repairable component (Sachan et al 2015b). In this research, cable is assumed to a repairable component.…”

Section: Effect Of Maintenancementioning

confidence: 99%

“…4, the failure probability of cables was obtained by NHPP. A detailed application of NHPP on power cable can be seen in Sachan et al (2015b). Let, failure distribution of cables homogenous in terms of voltage level, insulation material and installation year is where y is the failure time (age at which cable failed) and a is the age of the cables.…”

Section: Effect Of Maintenancementioning

confidence: 99%

“…The objective is achieved by solving bellman equations by backward induction for all the possible states which a system might visit in future (Sachan et al 2015c). The basic structure of bellman equation is as follows:…”

Section: Objective and Recursion Equation Formulationmentioning

confidence: 99%

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Probabilistic dynamic programming algorithm: a solution for optimal maintenance policy for power cables

Sachan

Zhou

2019

Life Cycle Reliab Saf Eng

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This paper presents a probabilistic dynamic programming algorithm to obtain the optimal cost-effective maintenance policy for a power cable. The algorithm determines the states which a cable might visit in the future and solves the functional equations of probabilistic dynamic programming by backward induction process. The optimisation model considers the probabilistic nature of cables failures. This work specifies the data needs, and presents a procedure to utilize maintenance data, failure data, cost data, and condition monitoring or diagnostic test data. The model can be used by power utility managers and regulators to assess the financial risk and schedule maintenance.

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Section: Length Of Maintenance Periodmentioning

confidence: 99%

Section: Effect Of Maintenancementioning

confidence: 99%

Section: Effect Of Maintenancementioning

confidence: 99%

Section: Objective and Recursion Equation Formulationmentioning

confidence: 99%

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Probabilistic dynamic programming algorithm: a solution for optimal maintenance policy for power cables

Sachan

Zhou

2019

Life Cycle Reliab Saf Eng

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“…In cases of age related failures, efforts have been made in using statistical tools for analysis of causes of early failures and for failure rate prediction [40, 41]. The former is important in taking the best decision during the procurement and installation, whilst the latter helps to optimise maintenance and replacement programs.…”

Section: Failure Causes and Statistical Analysismentioning

confidence: 99%

Review of recent research towards power cable life cycle management

Zhou

Dong

2017

High Voltage

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Power cables are integral to modern urban power transmission and distribution systems. For power cable asset managers worldwide, a major challenge is how to manage effectively the expensive and vast network of cables, many of which are approaching, or have past, their design life. This study provides an in-depth review of recent research and development in cable failure analysis, condition monitoring and diagnosis, life assessment methods, fault location, and optimisation of maintenance and replacement strategies. These topics are essential to cable life cycle management (LCM), which aims to maximise the operational value of cable assets and is now being implemented in many power utility companies. The review expands on material presented at the 2015 JiCable conference and incorporates other recent publications. The review concludes that the full potential of cable condition monitoring, condition and life assessment has not fully realised. It is proposed that a combination of physics-based life modelling and statistical approaches, giving consideration to practical condition monitoring results and insulation response to in-service stress factors and short term stresses, such as water ingress, mechanical damage and imperfections left from manufacturing and installation processes, will be key to success in improved LCM of the vast amount of cable assets around the world.

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