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Application of Big Data Technology in Protection Channel Interruption Analysis and Breaker Defect Identification

机译：大数据技术在保护信道中断分析和断路器缺陷识别中的应用

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Microcomputer protection indicated the protection device enter the intelligent era. Over years' operation, a huge amount of data has been accumulated. Unfortunately, mass data has not been used effectively. The development of Internet technology brings protection into information age. Two typical applications are presented in this paper. One is abnormal protection channel interruption analysis; the other is breaker defect identification. Combining the data of the Protection and Fault Recorder Management System (PFRMS) with the data of the Communication Network Management System (CNMS), abnormal interruption analysis of the protection channel is studied in this paper. It effectively extracts the channel anomaly events that need to be focused on by the protection engineer. As for breaker defect, the characteristics of each time link in the fault isolation process are analyzed. The wavelet transform is used to capture the separation moment of the contact. The arc extinguishing time is analyzed to evaluate the arc extinguishing chamber. By cluster analysis, each time duration of fault isolation is calculated, the abnormal points differ from others can be found out easily, which means there is an abnormality in the secondary circuit of the breaker.
机译：微电脑保护指示保护装置进入智能时代。超过数年的操作，已经积累了大量数据。不幸的是，群众数据尚未有效地使用。互联网技术的发展带来了信息时代的保护。本文提出了两个典型的应用。一个是异常保护信道中断分析;另一个是断路器缺陷识别。将保护和故障记录器管理系统（PFRMS）的数据与通信网络管理系统（CNMS）的数据相结合，在本文中研究了保护通道的异常中断分析。它有效地提取了保护工程师需要专注的信道异常事件。对于断路器缺陷，分析了故障隔离过程中每次链路的特性。小波变换用于捕获接触的分离力矩。分析电弧熄灭时间以评估电弧熄灭室。通过聚类分析，计算出故障隔离的每次持续时间，可以容易地发现异常点，这意味着断路器的次级电路存在异常。

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