Intelligent Online Partial Discharge Detection and Sensor

Author:

Zhu Rong1ORCID,Chen Zhaohui1ORCID,Liu Jingshuai1ORCID,Zhu Tao1ORCID,Du Xuan2ORCID

Affiliation:

1. Yili Xintian Coal Chemistry co., Ltd Bayandai Town Yining, Xinjiang 835000, China

2. Shanghai Proinvent Info Tech co., Ltd, Shanghai 200241, China

Abstract

In order to realize the online monitoring of partial discharge in solid switch cabinet, obtain the real partial discharge power and evaluate the insulation status of the switch cabinet, an online detection device based on partial discharge in solid switch cabinet was proposed. The ultrasonic sensor and resonant circuit used by the device to collect the high frequency signal generated when partial discharge occurs and the high frequency signal was converted into the voltage signal. The voltage signal was sent to the STM32 main control chip after data preprocessing and analog-to-digital conversion. Through the conversion of the collected electrical data, the local discharge quantity was obtained and displayed on LCD screen in real time. If the detected discharge power was greater than a set value, an alarm would be automatically issued to remind the on-site power personnel to pay attention to it and prevent major power accidents caused by insulation damage. From the experimental results, it was found that the value of intermittent partial discharge collected by the developed device was 63pC, which was basically consistent with the DMS data. The experimental results showed that the device had the characteristics of simple operation and signal processing speed, high testing data real-time, and low cost, which was suitable for the real-time monitoring of the high voltage equipment in internal partial discharge. It was convenient for operators to maintain the equipment and ensure the normal operation of the equipment, which was of great significance to improve the reliability of power supply.

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Retracted: Intelligent Online Partial Discharge Detection and Sensor;Wireless Communications and Mobile Computing;2023-09-20

2. IoT Edge-based Machine Learning Approach for Detection of Partial Discharge in Power Transformers;2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings);2023-09-16

3. Development of a Flexible Rogowski Coil Sensor for Partial Discharge Detection in Power Cables;2023 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET);2023-09-12

4. Audio General Recognition of Partial Discharge and Mechanical Defects in Switchgear Using a Smartphone;Applied Sciences;2023-09-09

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