Volume 42 Issue 12
Dec.  2020
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LIU Rong, LIU Hui, JIA Ran, ZHANG Yang, ZHOU Chao, LIU Chuanbin, SHEN Qinghe. Design of Intelligent Infrared Diagnosis System for Power Grid Equipment[J]. Infrared Technology , 2020, 42(12): 1198-1202.
Citation: LIU Rong, LIU Hui, JIA Ran, ZHANG Yang, ZHOU Chao, LIU Chuanbin, SHEN Qinghe. Design of Intelligent Infrared Diagnosis System for Power Grid Equipment[J]. Infrared Technology , 2020, 42(12): 1198-1202.

Design of Intelligent Infrared Diagnosis System for Power Grid Equipment

  • Received Date: 2020-04-03
  • Rev Recd Date: 2020-12-01
  • Publish Date: 2020-12-26
  • 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.
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