Abstract

Transformer is the most important equipment in the power system. The research and development of fault diagnosis technology for Internet of Things equipment can effectively detect the operation status of equipment and eliminate hidden faults in time, which is conducive to reducing the incidence of accidents and improving people's life safety index.

Objective

To explore the utility of Internet of Things in power transformer fault diagnosis system.

Methods

A total of 30 groups of transformer fault samples were selected, and 10 groups were randomly selected for network training, and the rest samples were used for testing. The matter-element extension mathematical model of power transformer fault diagnosis was established, and the correlation function was improved according to the characteristics of three ratio method. Each group of power transformer was diagnosed for four months continuously, and the monitoring data and diagnosis were recorded and analyzed result. GPRS communication network is used to complete the communication between data acquisition terminal and monitoring terminal. According to the parameters of the database, the working state of the equipment is set, and various sensors are controlled by the instrument driver module to complete the diagnosis of transformer fault system.

Results

The detection success rate of the power transformer fault diagnosis system model established in this paper is as high as 95.6%, the training error is less than 0.0001, and it can correctly identify the fault types of the non training samples. It can be seen that the technical support of the Internet of Things is helpful to the upgrading and maintenance of the power transformer fault diagnosis system.

中文翻译：

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基于物联网的电力变压器故障诊断系统

摘要

变压器是电力系统中最重要的设备。物联网设备故障诊断技术的研究与开发可以有效地检测设备的运行状态，及时消除隐患，有利于减少事故的发生，提高人们的生命安全指标。

目的

探索物联网在电力变压器故障诊断系统中的应用。

方法

总共选择了30组变压器故障样本，并随机选择10组进行网络训练，其余样本用于测试。建立了电力变压器故障诊断的物元扩展数学模型，并根据三比法的特点对相关函数进行了改进。每组电力变压器连续诊断四个月，监测数据和诊断记录并分析结果。GPRS通信网络用于完成数据采集终端与监控终端之间的通信。根据数据库的参数，设置设备的工作状态，并通过仪表驱动模块控制各种传感器，完成变压器故障系统的诊断。

结果

本文建立的电力变压器故障诊断系统模型的检测成功率高达95.6％，训练误差小于0.0001，可以正确识别非训练样本的故障类型。可以看出，物联网的技术支持有助于电力变压器故障诊断系统的升级和维护。