Methods for Remaining Life Prediction of Power Cable based on Partial Discharge and Cable Failure History Data

Zaeni, Arpan; Khayam, Umar; Viviantoro, Deny

doi:10.1109/iceei47359.2019.8988904

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…Most of these failures result from environmental factors. Traditional condition monitoring technologies for subsea cables are centered around internal failure modes, including partial discharge monitoring and distributed temperature sensing (DTS) monitoring, to detect cable overheating and electrical overload using embedded fibre optics [10,21,22]. However, these methods does not offer precursor indicators to cable failures, and does not monitor operating environment induced failures, such as abrasion and corrosion due to interactions between subsea cable, seabed, and tidal flows.…”

Section: Subsea Power Cable Standards and Condition Monitoringmentioning

confidence: 99%

Subsea Power Cable Health Management Using Machine Learning Analysis of Low-Frequency Wide-Band Sonar Data

Tang,

Brown,

Mitchell

et al. 2023

Energies

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Subsea power cables are critical assets for electrical transmission and distribution networks, and highly relevant to regional, national, and international energy security and decarbonization given the growth in offshore renewable energy generation. Existing condition monitoring techniques are restricted to highly constrained online monitoring systems that only prioritize internal failure modes, representing only 30% of cable failure mechanisms, and has limited capacity to provide precursor indicators of such failures or damages. To overcome these limitations, we propose an innovative fusion prognostics approach that can provide the in situ integrity analysis of the subsea cable. In this paper, we developed low-frequency wide-band sonar (LFWBS) technology to collect acoustic response data from different subsea power cable sample types, with different inner structure configurations, and collate signatures from induced physical failure modes as to obtain integrity data at various cable degradation levels. We demonstrate how a machine learning approach, e.g., SVM, KNN, BP, and CNN algorithms, can be used for integrity analysis under a hybrid, holistic condition monitoring framework. The results of data analysis demonstrate the ability to distinguish subsea cables by differences of 5 mm in diameter and cable types, as well as achieving an overall 95%+ accuracy rate to detect different cable degradation stages. We also present a tailored, hybrid prognostic and health management solution for subsea cables, for cable remaining useful life (RUL) prediction. Our findings addresses a clear capability and knowledge gap in evaluating and forecasting subsea cable RUL. Thus, supporting a more advanced asset management and planning capability for critical subsea power cables.

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Section: Subsea Power Cable Standards and Condition Monitoringmentioning

confidence: 99%

Subsea Power Cable Health Management Using Machine Learning Analysis of Low-Frequency Wide-Band Sonar Data

Tang,

Brown,

Mitchell

et al. 2023

Energies

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“…Based on industry standard fault location equipment and the knowledge of the operator, faults on subsea cables are often difficult to locate [7]. There are many fault diagnosis systems for subsea cables, which focus on internal failure modes due to partial discharge and localised heating from electrical overloading and/or degradation of internal insulation materials [31][32][33][34]. However, these systems are not able to predict the expected lifetime, of a cable section subjected to various wear-out mechanisms [35].…”

Section: Introductionmentioning

confidence: 99%

Non-destructive examination (NDE) methods for dynamic subsea cables for offshore renewable energy

et al. 2022

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Offshore renewable energy installations are moving into more challenging environments where fixed foundations are not economically viable, forcing the development of floating platforms. Subsea cables are critical for transfer of the power generated back to shore. The electrical capabilities of subsea cables are well understood; however, the structural capabilities are not, subsea power cable failures accounting for a significant proportion of insurance claims. Cables are challenging to repair, with specific vessels and good weather windows required, therefore making operations very costly. A good understanding of the internal structure of a subsea cable, and interaction between the layers, is integral to the development of robust and reliable, high voltage, dynamic, subsea cables. A requirement therefore exists for non-destructive examination (NDE) of live subsea cables to determine locations, and identify the causes, of faults and classify their type. An NDE framework such as this would assist in planning operations and reduce the risk and cost inherent to delivering offshore power. Improved understanding of subsea cable failure modes and mechanisms could also be achieved through us of NDE during onshore, dry, experimental testing. Three currently available NDE methods are considered, developed for use in other disciplines, for the purpose of structural monitoring of subsea power cables during onshore evaluation testing. The NDE methods were: i) thermography, ii) eddy current testing (ECT), iii) spread spectrum time domain reflectometry (SSTDR). The methods are assessed with regards to the information that could be obtained from both a static and oscillating cable in pilot physical tests. The results of the testing were promising, with cable motions and interlayer movements being detected by all techniques to various degrees.

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“…For this reason, electrical engineers are currently focused on the development of remote monitoring devices devoted to electrical grid parameters, together with advancements in modeling to address the ageing phenomena. These models are necessary when relevant parameters have to be found for remaining life assessment (RLA) of the device under study and, from there, planning reliability strategies to minimize the outages, which results in energy and economical losses [1,2].…”

Section: Introductionmentioning

confidence: 99%

An Innovative Sensor for Cable Joint Monitoring and Partial Discharge Localization

et al. 2021

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To enhance grid reliability, weak points must be monitored. One of the weaknesses is the cable joints, which are prone to failure and can cause great losses from both a technical and economical point of view. Joints failures are usually caused by impurities unintentionally added during installation that cause partial discharges (PDs). In time, these discharges erode the insulation and generate treeing up to a destructive discharge between the conductor and the ground shield. For this reason, a method for the early detection of defects in joint installation and their online monitoring is required. A previously developed sensor was improved by adapting it for this purpose. It is based on the measurement of the induced current on a conductor due to a charge variation. It was experimentally tested on an actual joint in which defects were artificially introduced. Results show that the sensor is able to detect partial discharges. Moreover, a method for PD localization was developed. The first results show a coherency between the possible defect location, numerical simulations and historical background.

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Methods for Remaining Life Prediction of Power Cable based on Partial Discharge and Cable Failure History Data

Cited by 4 publications

References 10 publications

Subsea Power Cable Health Management Using Machine Learning Analysis of Low-Frequency Wide-Band Sonar Data

Subsea Power Cable Health Management Using Machine Learning Analysis of Low-Frequency Wide-Band Sonar Data

Non-destructive examination (NDE) methods for dynamic subsea cables for offshore renewable energy

An Innovative Sensor for Cable Joint Monitoring and Partial Discharge Localization

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