Advanced solution for on-site diagnosis of distribution power cables

Petzold, Frank; Schlapp, Hubert; Gulski, Ε.; Seitz, P.N.; Quak, B.

doi:10.1109/tdei.2008.4712661

Cited by 26 publications

(8 citation statements)

References 5 publications

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“…The joining of electrical cable connections, which is normally done on-site, is prone to human error owing to placement problems and contamination [18]. This susceptibility to errors during joint construction underscores the influence of personal factors.…”

Section: Fabrication Of Artificial Defectsmentioning

confidence: 99%

Study of partial discharges measurement cycles effect on defect recognition for underground cable joints

Chang,

Boyanapalli

2024

Meas. Sci. Technol.

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This study investigates the influence of various partial discharge (PD) measurement durations on defect recognition in high voltage power cable joints, aiming to address a crucial challenge in the field of insulation assessment. The main objective is to determine the optimal measurement cycle duration for accurate defect recognition, thereby enhancing the reliability of PD-based diagnostic techniques. Totally 14 cable joints, each containing three different types of prefabricated artificial defects, were analyzed across five different measurement cycle durations: 40, 80, 120, 200, and 1200 cycles. Subsequently, Convolutional Neural Networks (CNNs) were employed for defect recognition analysis. The results reveal a significant impact of measurement cycle duration on defect recognition accuracy. Particularly, a CNN based on 200 measurement cycles demonstrates superior performance compared to models with fewer cycles, achieving a total defect recognition accuracy of 100%. This finding underscores the importance of sufficient measurement cycles for obtaining comprehensive PRPD patterns and accurate defect classification. Furthermore, the study highlights the significance of setting a threshold value to mitigate false conditions in defect type recognition, offering valuable insights for practical applications in power system maintenance and diagnostics. Overall, this research contributes to advancing the understanding of PD-based insulation assessment techniques and provides practical recommendations for optimizing measurement cycle duration to enhance defect recognition accuracy in high voltage power cable joints.

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Section: Fabrication Of Artificial Defectsmentioning

confidence: 99%

Study of partial discharges measurement cycles effect on defect recognition for underground cable joints

Chang,

Boyanapalli

2024

Meas. Sci. Technol.

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“…PD detection can be effectively employed to check whether an onsite test had a destructive impact on the insulation system. In [86], the influence of attenuation and the dispersive effects of cable characteristics for PD diagnosis was investigated. Energizing the PILC and XLPE cables with damped AC voltage demonstrated the relevant demands for field application of PD diagnosis.…”

Section: Partial Discharge Detection Of Overhead Cablesmentioning

confidence: 99%

Power Distribution System Faults and Wildfires: Mechanisms and Prevention

Bandara

Rajeev

Gad

2023

Forests

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Wildfires are one of the most hazardous natural disasters in Australia in terms of fatalities, property damage and financial losses. Events of catastrophic wildfires are recorded across the world including in the United States and Canada. Failures along power distribution infrastructure and network faults have been identified as some of the causes for the initiation of wildfires. Thus, it is critical to better understand the mechanisms and the potential prevention strategies for wildfires caused by power distribution system faults. In this light, this paper presents how the power distribution network faults cause wildfires highlighting the main mechanisms. Further, this paper reviewed studies on recent advancements for the prediction, detection and prevention of wildfires. Condition assessment of power distribution infrastructure including poles, crossarms, overhead cables and other attachments are paramount to detect potential defects and to carry out timely replacements which can subsequently mitigate the possibility of wildfire initiation. Therefore, this paper summarized the studies on condition monitoring and surveillance techniques for power distribution infrastructure. Altogether, this paper aimed to enhance the awareness about the prevention strategies for wildfires caused by power distribution system faults.

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“…To prevent major accidents, it is essential to have real-time knowledge of the equipment's condition. In the operation of the power system, the high-voltage power equipment is responsible for the supply, transmission, and distribution of electricity [1][2][3][4]. Given the increasing complexity of the power system and the demand for power going up, insulation defects of high-voltage power equipment will cause serious power outages, equipment damage, economic loss, and inconvenience to the industry, and even equipment failure and human casualties.…”

Section: Introductionmentioning

confidence: 99%

Research on a Partial Discharge Expert System for the Diagnosis of Damaged Transformation Equipment

Tsai,

Hsueh,

Chen

et al. 2024

Applied Sciences

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Partial discharge (PD) characteristics are very important for the diagnosis of damaged transformation equipment. If the power transmission and transformation equipment fails, it will cause large economic losses, and thus prevention is better than treatment. One of the effective methods for high-voltage insulation degradation detection is to observe the phenomenon of partial discharge of equipment, which is the earliest characteristic. Prevention can be carried out in advance, and trend observation is better than periodic inspection. Long-term observation can effectively reduce the probability of misjudgment. This project intends to develop a high-speed data-acquisition device to acquire the original discharge waveform data of partial discharge for noise suppression. In order to improve the diagnostic efficiency and accuracy of the diagnostic system, it is necessary to suppress the noise of the measurement data, so as to carry out the fault identification of the discharge type. Through this method, the actual operating data of the system can be recorded as the original discharge waveform, in order to understand the original discharge waveform conditions of the power transmission and transformation equipment in multiple partial discharge measurements, and then after noise suppression, it can be regarded as a type of partial discharge identification.

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Advanced solution for on-site diagnosis of distribution power cables

Cited by 26 publications

References 5 publications

Study of partial discharges measurement cycles effect on defect recognition for underground cable joints

Study of partial discharges measurement cycles effect on defect recognition for underground cable joints

Power Distribution System Faults and Wildfires: Mechanisms and Prevention

Research on a Partial Discharge Expert System for the Diagnosis of Damaged Transformation Equipment

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