电气工程学报 ›› 2021, Vol. 16 ›› Issue (4): 189-195.doi: 10.11985/2021.04.024

• 电力系统 • 上一篇    下一篇

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低压开关柜运行在线监测和诊断系统设计

王建新(), 李铁军(), 朱军(), 杜一锦()   

  1. 国网冀北电力有限公司廊坊供电公司 廊坊 350001
  • 收稿日期:2020-12-01 修回日期:2021-10-11 出版日期:2021-12-25 发布日期:2022-02-10
  • 作者简介:王建新,男,1978年生,硕士,高级工程师。主要研究方向为高压试验技术、状态检修管理。E-mail: rtgpo4om@21cn.com
    李铁军,男,1973年生,工程师。主要研究方向为电力运行、维护、检修。E-mail: 15921036681@163.com
    朱军,男,1986年生,硕士,工程师。主要研究方向为高压试验技术、状态检修管理。E-mail: 13937408280@163.com
    杜一锦,女,1988年生,初级工程师。主要研究方向为运检专业变电设备相关管理。E-mail: 19945603262@163.com

Design of On-line Monitoring and Diagnosis System for Low-voltage Switchgear Operation

WANG Jianxin(), LI Tiejun(), ZHU Jun(), DU Yijin()   

  1. Langfang Power Supply Company, State Grid Jibei Electric Power Co., Ltd., Langfang 350001
  • Received:2020-12-01 Revised:2021-10-11 Online:2021-12-25 Published:2022-02-10

摘要:

针对于低压开关柜人工巡检成本高、效率低下的问题,设计一种低压开关柜运行状态与检测故障在线监测系统。该系统通过传感器获取低压开关柜的运行数据,采用云样本熵的方法对数据进行处理,获取其正常运行和故障运行的特征值,对特征值使用马氏距离算法进行计算。该方法首先通过训练样本寻找马氏距离的阈值,再通过试验样本数据计算马氏距离,马氏距离的值介于7~9,最后将该距离使其与马氏距离的阈值进行比较,进而可以实时、在线监测其运行状态。试验表明,该系统的故障检测正确率大于98%。

关键词: 低压开关柜, 智能电网, 云样本熵, 马氏距离, 在线监测

Abstract:

Aiming at the problem of high cost and low efficiency of manual inspection of low-voltage switchgear, a system that can detect the operating status and faults of low-voltage switchgear online is researched. The system obtaines operating data of low-voltage switchgear through sensors. The data is processed by the method of cloud sample entropy, and the characteristic values of its normal operation and fault operation are obtained. The eigenvalues are calculated by using Mahalanobis distance algorithm. The Mahalanobis distance threshold is obtained through the training samples, and then the Mahalanobis distance from the experimental sample data is calculated. The Mahalanobis distance is between 7-9, and finally the distance is compared with the Mahalanobis distance threshold, realizing real-time and online monitoring of its operating status. Experiments show that the fault detection accuracy rate of this system is greater than 98%.

Key words: Low voltage switchgear, smart grid, cloud sample entropy, Mahalanobis distance, online monitoring

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