Effect of disconnector and high‐voltage conductor on propagation characteristics of PD‐induced UHF signals

Shi, Minxia; Han, Xutao; Zhang, Xuanrui; Zhang, Zheming; Li, Junhao

doi:10.1049/hve.2017.0169

Cited by 20 publications

(8 citation statements)

References 11 publications

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“…By effective detection of these signals, PD in the GIS can be reflected [31]. At present, the conventionally used PD detection methods include pulse current method, ultra‐high frequency method and ultrasonic method [32, 33]. However, electric sensors are mainly used in these methods, which are subject to EM interference on site.…”

Section: Pd Detection With Optical Methodsmentioning

confidence: 99%

Optical sensing in condition monitoring of gas insulated apparatus: a review

et al. 2019

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Health monitoring of gas insulated apparatus is critical to improve the reliability and to reduce the life cycle cost. Among the various methods for monitoring, optical sensing developed fast in recent years due to their highly sensitive and antielectromagnetic interference behaviour. This study reviews the optical monitoring methods for partial discharge, gas concentration and temperature of gas insulted apparatus. In addition, the challenges of sensor development are carefully discussed here. The future prospects of optical monitoring of gas insulated apparatus are also analysed to inspire new ideas.

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Section: Pd Detection With Optical Methodsmentioning

confidence: 99%

Optical sensing in condition monitoring of gas insulated apparatus: a review

et al. 2019

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“…It can be seen that the TEM mode does not have a longitudinal component (z-direction), and the velocity of the wave is not frequency dependent. On the contrary, TE (and TM) mode has cutoff frequencies below which waves cannot propagate [62]. The cutoff frequencies for the TE and TM modes of coaxial waveguides are calculated using the following equations [63]:…”

Section: Disconnecting Parts and Change Of Radii Ratiomentioning

confidence: 99%

On the Electromagnetic Wave Behavior Due to Partial Discharge in Gas Insulated Switchgears: State-of-Art Review

et al. 2019

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The rapid growth of gas insulated switchgears as a compact, efficient, and reliable device has recently been given great attention. Albeit gas insulated switchgears can seldom suffer from failure due to the high resiliency and robustness, some severe damages have been experienced by such devices particularly in the event of partial discharge. Thus, monitoring such accidents has become a vital part of power systems reliability. The ultra-high frequency techniques have recently shown superior performance in the detection and classification of electromagnetic waves produced by partial discharge. This is mainly due to the great immunity to the noise of the ultra-high frequency detection techniques compared with the veryhigh-frequency counterparts. This review paper highlights the mathematical aspects of the electromagnetic waves generated by partial discharge. It also delivers an overview of the electromagnetic wave behavior in the complex structure of gas insulated switchgears, and outlines the important characteristics of the internal and external partial discharge detection using ultra-high frequency methods. INDEX TERMS Electromagnetic waves behavior, finite difference time domain, gas insulated switchgears, partial discharge, sensors, ultra-high frequency measurements.

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“…There are many ways to detect bushing failures, including dielectric loss measurement, UHF (ultra‐high frequency) method [6], FDS (frequency domain spectroscopy) technique [7], infrared image diagnosis [8], etc. The dielectric loss measurement requires off‐line preventive tests, which would affect the stability of the power apparatus.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis of the bushing infrared images based on mask R‐CNN and improved PCNN joint algorithm

Jiang

Bie

et al. 2020

High Voltage

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Bushings are served as an important component of the power transformers; it's of great significance to keep the bushings in good insulation condition. The infrared images of the bushing are proposed to diagnose the fault with the combination of image segmentation and deep learning, including object detection, fault region extraction, and fault diagnosis. By building an object detection system with the frame of Mask Region convolutional neural network (CNN), the bushing frame can be exactly extracted. To distinguish the fault region of bushings and the background, a simple linear iterative clustering‐based pulse coupled neural network is proposed to improve the fault region segmentation performance. Then, two infrared image feature parameters, the relative position and area, are explored to classify fault type effectively based on the K‐means cluster technique. With the proposed joint algorithm on bushing infrared images, the accuracy reaches 98%, compared with 44% by the conventional CNN classification method. The integrated algorithm provides a feasible and advantageous solution for the field application of bushing image‐based diagnosis.

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Effect of disconnector and high‐voltage conductor on propagation characteristics of PD‐induced UHF signals

Cited by 20 publications

References 11 publications

Optical sensing in condition monitoring of gas insulated apparatus: a review

Optical sensing in condition monitoring of gas insulated apparatus: a review

On the Electromagnetic Wave Behavior Due to Partial Discharge in Gas Insulated Switchgears: State-of-Art Review

Fault diagnosis of the bushing infrared images based on mask R‐CNN and improved PCNN joint algorithm

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