Online Monitoring of Electrical Equipment Condition Based on Infrared Image Temperature Data Visualization

Abstract

Temperature is one of the most common indicators for the health of electrical equipment in the substation. By now, infrared thermography has been an important monitoring tool due to its real-time temperature measurement and noncontact manner. However, at present, portable thermal imagers are usually used to collect and store the status image of single equipment at a certain time, which cannot continuously track the condition of the equipment and the efficiency is very low. In order to solve this problem, our team proposed a method for online condition of electrical equipment based on the visualization and processing of infrared image temperature data. We developed video inspection software, equipped with an infrared camera for automatic inspection to obtain infrared images. After that, the target equipment in a whole image are automatically extracted based on the reference image and the equipment type of each target is classified. Then, in order to visualize temperature data and extract temperature information for different types of equipment, the concepts of heating spot, heating section, and heating area are defined. Finally, diagnosis rules based on relevant related thermal fault diagnosis standards and past experience are proposed to evaluate the condition of each target equipment, using the temperature rise and heat generation percentage. The method has been applied in a real substation and proved its effectiveness.

Research on layout method of monitoring camera in non-direct-view area of substation

“…After setting the farthest recognition point of the camera, the corresponding effective sensing area is calculated based on the predicted coverage area monitored by the non-direct-view area [15]. First, measure the vertical distance from the farthest monitoring point to the lens, and generally control it between 6.5 and 7.5m [16]. Subsequently, different recognition layout environments are set, and the actual width of the farthest recognized object is adjusted from 5.5m to 8.5m, and the pixel width of the farthest recognized object is 2.5m [17].…”

A Hierarchical Maintenance Method for Power System Transmission and Substation Multi-Equipment Operation Status Considering Equipment Service Age

“…Among the information resources stored in the unified information-sharing platform of power plants, all information related to the operation status of transmission and substation equipment can be roughly divided into four categories: historical fault information (mainly recording the types of faults and maintenance records of equipment that have occurred during operation), static basic data (including the limitation thresholds and initial values of commissioning tests given in the protocol documents for equipment-related characteristics), pre-inspection test data (mainly including data collected during periodic pre-inspection tests of equipment) and real-time monitoring data (mainly referring to the characteristics data fed back and stored in real time during the operation of equipment, mainly including data collected during periodic pre-testing of equipment) and real-time monitoring data (mainly referring to real-time feedback and stored characteristics data of equipment during operation) [9]. In the evaluation process of equipment operation status, different data reflect the health level of the equipment at different time points or different performance aspects: static basic data describe the overall health status of the equipment when it is put into use (generally reflecting the optimal state of the equipment operation), and the range of values corresponding to each index when the equipment is in normal operation; pre-test and real-time monitoring data reflect the health level of the equipment when the pre-test and real-time monitoring data reflect the health status of the equipment in the process of periodic inspection and a real-time operation corresponding to different performance.…”

Thermal fault diagnosis of complex electrical equipment based on infrared image recognition

“… 4 . Prompt and accurate detection of abnormal temperatures is vital for assessing the operational status of electrical equipment, playing a crucial role in maintaining the safety and stability of substations 5 .…”