On-line PD Monitoring System (PDLOOK) for XLPE Cables

Akaiwa, Shigeru; Miyagawa, Koji; Nakashima, Toshihiko; Sakoda, Tatsuya; Miyake, Tetsuo; Takayama, Akira

doi:10.23919/cmd54214.2022.9991514

Cited by 2 publications

(3 citation statements)

References 1 publication

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“…Data acquisition systems subsequently process the sensor data. Finally, the fault detection and diagnosis systems identify the type of fault and provide a clear maintenance indication [12].…”

Section: Condition Monitoring and Pd Signalsmentioning

confidence: 99%

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A Review on the Classification of Partial Discharges in Medium-Voltage Cables: Detection, Feature Extraction, Artificial Intelligence-Based Classification, and Optimization Techniques

Kumar,

Shafiq,

Kauhaniemi

et al. 2024

Energies

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Medium-voltage (MV) cables often experience a shortened lifespan attributed to insulation breakdown resulting from accelerated aging and anomalous operational and environmental stresses. While partial discharge (PD) measurements serve as valuable tools for assessing the insulation state, complexity arises from the presence of diverse discharge sources, making the evaluation of PD data challenging. The reliability of diagnostics for MV cables hinges on the precise interpretation of PD activity. To streamline the repair and maintenance of cables, it becomes crucial to discern and categorize PD types accurately. This paper presents a comprehensive review encompassing the realms of detection, feature extraction, artificial intelligence, and optimization techniques employed in the classification of PD signals/sources. Its exploration encompasses a variety of sensors utilized for PD detection, data processing methodologies for efficient feature extraction, optimization techniques dedicated to selecting optimal features, and artificial intelligence-based approaches for the classification of PD sources. This synthesized review not only serves as a valuable reference for researchers engaged in the application of methods for PD signal classification but also sheds light on potential avenues for future developments of techniques within the context of MV cables.

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Section: Condition Monitoring and Pd Signalsmentioning

confidence: 99%

“…As the focus of this paper is PD source identification, Figure 1 shows the developed PD defects/sources. detection and diagnosis systems identify the type of fault and provide a clear maintenance indication [12].…”

Section: Condition Monitoring and Pd Signalsmentioning

confidence: 99%

A Review on the Classification of Partial Discharges in Medium-Voltage Cables: Detection, Feature Extraction, Artificial Intelligence-Based Classification, and Optimization Techniques

Kumar,

Shafiq,

Kauhaniemi

et al. 2024

Energies

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“…The increasing urban development has led to a continuous rise in the usage of cables [1][2][3], especially under high-voltage transmission levels. It has brought about numerous challenges for cable testing and rapid repair.…”

Section: Introductionmentioning

confidence: 99%

Electric Field in Metal Stress Cone of Cable Quick Repair/Test Joint

Sun,

Zhang,

Zhao

et al. 2023

J. Phys.: Conf. Ser.

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In order to expedite power restoration after cable failures, a plug-in GIS (Gas Insulated Switchgear) intermediate joint is designed for cable quick repair/test. During the electric field simulation of this intermediate joint, significant electric field distortions were observed at the metal stress cones and the cable’s semi-conductive layer discontinuity, indicating potential weak points in insulation. To mitigate the electric field distortions within the joint, investigations were conducted on the impact of factors such as the gap width between the metal stress cones and the XLPE cable, the relative position of the semi-conductive layer discontinuity, the stress cone, and the winding length of high dielectric constant tape. The design and installation scheme of the metal stress cone wasa obtained through simulation, which provides a basis for the design and manufacture of the GIS quick repair/test joint.

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On-line PD Monitoring System (PDLOOK) for XLPE Cables

Cited by 2 publications

References 1 publication

A Review on the Classification of Partial Discharges in Medium-Voltage Cables: Detection, Feature Extraction, Artificial Intelligence-Based Classification, and Optimization Techniques

A Review on the Classification of Partial Discharges in Medium-Voltage Cables: Detection, Feature Extraction, Artificial Intelligence-Based Classification, and Optimization Techniques

Electric Field in Metal Stress Cone of Cable Quick Repair/Test Joint

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