B 2014, 'Analysis of significant factors on cable failure using the Cox proportional hazard model', IEEE Transactions on Power Delivery, vol. 29, no. 2, pp. 951-957. https://doi. Abstract-This paper proposes the use of the Cox ProportionalHazard Model (Cox PHM), a statistical model, for the analysis of early-failure data associated with power cables. The Cox PHM analyses simultaneously a set of covariates and identifies those which have significant effects on the cable failures. In order to demonstrate the appropriateness of the model, relevant historical failure data related to Medium Voltage (MV, rated at 10kV) distribution cables and High Voltage (HV, 110kV and 220kV) transmission cables have been collected from a regional electricity company in China. Results prove that the model is more robust than the Weibull distribution in that failure data does not have to be homogeneous. Results also demonstrate that the method can single out a case of poor manufacturing quality with a particular cable joint provider by using the hypothesis test of p-value (5%). The proposed approach can potentially help to resolve any legal dispute that may arise between a manufacturer and a network operator, in addition to providing guidance for improving future practice in cable procurement, design, installations and maintenance. Index Terms-power cable, cable failures, Cox ProportionalHazard Model, hazard function, influencing factors, covariate.

Partial discharge (PD) testing of high voltage (HV) cables and cable accessories has been implemented predominantly using high frequency current transformers (HFCTs) as PD sensors. PD currents initiating at PD sources are coupled onto cable conductors and travel away from the PD sources and will be detected by HFCTs installed at cable terminations. In this paper, based on combining finite-difference time-domain (FDTD) modeling and transfer function theory, a hybrid modeling approach is proposed to investigate the processes of PD coupling and detection involved in HFCT-based PD testing of HV cables. This approach allows exciting a PD event anywhere in FDTD models of the cables and predicting output from HFCTs some distance away. Implementation of the method is illustrated using an 11 kV XLPE cable. Moreover, a "direct measurement" method to obtain original PD pulses as the excitation source waveform is presented. The modeling approach introduced here will facilitate studies on the relationship between measured PD signals and those excited at PD sources, which can potentially give useful insight into the basic mechanisms behind PD detection in cables.Index Terms--Finite-difference time-domain (FDTD), transfer functions, high frequency current transformer (HFCT), partial discharge (PD), power cables. [2017]102.

Artificial neural networks have been investigated for many years as a technique for automated diagnosis of defects causing partial discharge (PD). While good levels of accuracy have been reported, disadvantages include the difficulty of explaining results, and the need to hand-craft appropriate features for standard two-layer networks. Recent advances in the design and training of deep neural networks, which contain more than two layers of hidden neurons, have resulted in improved results in speech and image recognition tasks. This paper investigates the use of deep neural networks for PD diagnosis. Defect samples constructed in mineral oil were used to generate data for training and testing. The paper demonstrates the improvements in accuracy and visualization of learning which can be gained from deep learning

Power cables are preferred in urban areas for power transmission and distribution because of their high reliability, environmental friendliness and the visual invisibility. Whilst the volume of underground power cable has been growing steadily, the voltage level of the power cables have also increased significantly in recent years. The increasing volume of high voltage power cables brings about technical challenges to the power system operators and maintenance engineers. One of these challenges is the application of appropriate condition monitoring techniques to detect incipient cable faults and to reduce unplanned outages. This paper aims to analyse the causes, modes and mechanisms, among cable joint failures, and to propose an applicable sheath circulating current monitoring technique with the associated criteria for fault diagnosis. Two joint faults, flooded link box and joint insulation breakdown, are analysed in detail. Finally, a set of criteria is proposed for cable joint fault diagnosis based on the simulation of an 110kV underground power cable system of length 1.5km

This paper addresses the detection and localization of partial discharge (PD) in crossbonded (CB) high voltage (HV) cables. A great deal has been published in recent years on PD based cable insulation condition monitoring, diagnostics and localization in medium voltage (MV) and high voltage (HV) cables. The topic of pulse propagation and PD source localization in CB HV cable systems has yet to be significantly investigated. The main challenge to PD monitoring of CB HV cables is as a result of the interconnectedness of the sheaths of the three single phase cables. The cross-bonding of the sheaths makes it difficult to localize which of the three phases a PD signal has emanated from. Co-axial cables are used to connect cable sheaths to cable link boxes, for ease of installation and protection against moisture. A second challenge is, therefore, the coupling effect when a PD pulse propagates in HV cable joints and the co-axial cables, making PD detection and localization more complex. The paper presents experimental investigations into PD pulse coupling between the cable center conductor and the sheath and the behavior of PD pulse propagation in CB HV cables. It proposes a model to describe PD pulse propagation in a CB HV cable system to allow monitoring and localization, and also presents the knowledge rules required for PD localization in CB HV cable systems