Comparison of Surface Flashover Characteristics of Rod and Rib Type Post Insulator for Extra-High Voltage Superconducting Fault Current Limiter

Koo, Ja-Yoon; Shin, Woo-Ju; Oh, Dong-Hun; Hwang, Ryul; Lee, Bang-Wook

doi:10.1109/tasc.2017.2667892

Cited by 8 publications

(3 citation statements)

References 10 publications

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“…A huge number of line insulators are adopted on the lines. The occurrence of zero insulators is ascribed to the limited inspection range, resulting in the delay of discovery and replacement and eventually leading to serious power accidents [11][12][13]. The insulator grounding current comprehensively re ects the deterioration degree of the electrical performance.…”

Section: Introductionmentioning

confidence: 99%

Location prediction model of zero value insulator based on PNN

Wang

et al. 2023

Electr Eng

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Zero insulators directly reduce the electrical performance of insulator strings, affecting the safe and reliable operation of transmission lines. The grounding current of the insulator string contains the characteristic information of insulator electrical performance. Extracting the characteristic information of grounding current can realize the detection of zero value insulator, which is of great signi cance to ensure the safe operation of transmission lines. In this paper, the composite insulator used on ultra high voltage (UHV) lines is studied to analyze the in uence of zero insulators on the electric eld distribution.Furthermore, the corresponding characteristics of the zero insulators at different locations are extracted. The tting relationship between the characteristic quantity and the zero-insulator position is analyzed.The effective characteristics of grounding current are selected as training sample to establish the zeroinsulator position prediction model based on probabilistic neural network (PNN). The research result is meaningful for the detection of zero insulators.

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Section: Introductionmentioning

confidence: 99%

Location prediction model of zero value insulator based on PNN

Wang

et al. 2023

Electr Eng

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“…The spark or electric arc in the flashover channel causes the partial overheating of the insulation surface, and further leads to carbonization, decoloration, tracking, and damages to the surface of insulators. As a result, safe power transmission cannot be guaranteed if the damaged areas of insulators cannot be detected and replaced in a timely manner [4,5]. However, the accurate and timely detection and location of flashover faults on insulators is non-trivial.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, safe power transmission cannot be guaranteed if the damaged areas of insulators cannot be detected and replaced in a timely manner [4,5]. However, the accurate and timely detection and location of flashover faults on insulators is non-trivial.…”

Section: Introductionmentioning

confidence: 99%

Multi-Saliency Aggregation-Based Approach for Insulator Flashover Fault Detection Using Aerial Images

et al. 2018

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Accurate and timely detection of insulator flashover on power transmission lines is of paramount importance to power utilities. Most available solutions mainly focus on the exploitation of the flashover mechanism or the discharge area detection, rather than the identification of a damaged area due to flashovers using captured aerial images. To this end, this paper proposes a multi-saliency aggregation-based porcelain insulator flashover fault detection approach. The target area of the insulator is determined using the Faster-Pixelwise Image Saliency by Aggregating (F-PISA) algorithm based on the color and structural features. The color model can be established based on the color feature of the damaged areas on the insulator surface, and hence the damaged area can be identified. Based on the information obtained above, the contour information can be extracted. With the preceding process, the fault location can be confirmed with a good accuracy. The performance of the proposed detection approach is assessed through a comparative study with other available solutions. The numerical result demonstrates that the suggested solution can detect the insulator flashover with improved performance in terms of the average detection rate and average efficient detection rate. Additional analysis is carried out to evaluate its robustness and real-time performance, which confirms its deployment feasibility in practice.

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An intelligent recognition system for insulator string defects based on dimension correction and optimized faster R-CNN

Lin

Liu

2020

Electr Eng

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Comparison of Surface Flashover Characteristics of Rod and Rib Type Post Insulator for Extra-High Voltage Superconducting Fault Current Limiter

Cited by 8 publications

References 10 publications

Location prediction model of zero value insulator based on PNN

Location prediction model of zero value insulator based on PNN

Multi-Saliency Aggregation-Based Approach for Insulator Flashover Fault Detection Using Aerial Images

An intelligent recognition system for insulator string defects based on dimension correction and optimized faster R-CNN

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