The Detection Efficiency Improvement of the Distribution Equipment Based on the Intelligent Industrial Technology
2. State Grid Shandong Electric Power Company, Jinan, China
Abstract—With the rapid development of distribution network automation, the efficiency of the production, operation and management of equipment in distribution network need to be improved. The intelligent distribution network equipment includes the distribution terminal and the distribution overhead line malfunction indicator, which are important to the reliability of the power system. It is necessary to ensure the superior performance and reliability of the distribution terminal and malfunction indicator products. So, batch inspection need to be carried out. In this paper, the intelligent industrial automatic technology is used to detect the malfunction indicators and distribution terminals to improve detection efficiency. An intelligent industrial detection system is proposed for the batch inspection of distribution network equipment. The system is mainly composed of the automatic detection assembly line, the integrated management system and the control system. The appearance structure inspection, function performance test, data statistics, multi-dimensional analysis and the multiplex display can be performed by the assembly line. Based on the artificial intelligence vision recognition technology, the industrial robot technology and the big data analysis technology, the proposed system realizes the multi-level interaction of the detection procedure, improve the detection speed, and secures the accuracy of the equipment detection. The intelligent detection system is a pilot project for the large-scale and high-precision inspection of the distribution network equipment.
Index Terms—process control, intelligent detection, distribution terminal, malfunction indicator, integrated control systemCite: Lisheng Li, Yan Wen, Hailei Meng, Di Fan, Zhimin Shao, and Shidong Zhang, "The Detection Efficiency Improvement of the Distribution Equipment Based on the Intelligent Industrial Technology," Journal of Industrial and Intelligent Information, Vol. 7, No. 2, pp. 42-47, December 2019. doi: 10.18178/jiii.7.2.42-47