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一种智能型电网设备红外诊断系统的设计
引用本文:刘嵘,刘辉,贾然,张洋,周超,刘传彬,沈庆河.一种智能型电网设备红外诊断系统的设计[J].红外技术,2020,42(12):1198-1202.
作者姓名:刘嵘  刘辉  贾然  张洋  周超  刘传彬  沈庆河
作者单位:国网山东省电力公司电力科学研究院,山东 济南 250002
摘    要:目前广泛开展的电网红外诊断工作,受检测环境及人员专业水平的影响较大,广泛使用的红外热像仪自动化、智能化水平还不够高。本文提出了一种智能型电网设备红外诊断系统,系统包括环境参数模块、测距模块、设备类型识别模块、设备材料判断模块、发射率设置模块、测温模块、报告生成模块。系统自动检测环境温度、湿度、风速、与设备的检测距离,自动识别设备材料类型确定发射率,将以上参数自动在热像仪中进行设置。热像仪通过图像识别判断设备类型,按照该类设备红外诊断标准的判断方法和准则,自动读取设备相应位置的温度数据,计算得出检测结论。系统不仅减少了红外检测人员携带装备数量,而且实现了仪器检测参数自动设置、设备类型智能识别、检测结论自动生成,降低了对检测人员专业水平的要求。

关 键 词:电网设备  红外诊断  参数自动设置  智能识别  自动测温
收稿时间:2020-04-03

Design of Intelligent Infrared Diagnosis System for Power Grid Equipment
Affiliation:State Grid Shandong Electric Power Research Institute, Jinan 250002, China
Abstract:The widely used infrared diagnosis of power grids is significantly influenced by the detection environment and professional level of personnels. The automation and intelligence level of conventional infrared thermal imagers are not sufficiently high. Therefore, this paper presents an intelligent infrared diagnosis system for power grid equipment, which includes an environment parameter module, ranging module, equipment type identification module, equipment material judgment module, radiation rate setting module, temperature measurement module, and report generation module. The system automatically detects the ambient temperature, humidity, wind speed, and detection distance with the equipment, as well as automatically identifies the equipment material type, determines the radiation rate, and automatically sets the aforementioned parameters in the thermal imager. The thermal imager judges the equipment type through image recognition, automatically reads the temperature data of the corresponding position of the equipment according to the judgment method and criterion of the infrared diagnosis standard of the equipment, and obtains the detection conclusion by calculation. It not only reduces the number of instruments required to be carried by the infrared detection personnel, but also realizes the automatic setting of instrument detection parameters, with intelligent identification of equipment types and automatic generation of detection conclusions, thereby reducing the level of professional requirements for detection personnel.
Keywords:
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