Open AccessDesign and Application of Intelligent Unmanned Spot Inspection System in Thermal Power Plant
Author(s) -
Yinke Yang,
Kaifeng Chen,
Zhanyuan Wu,
Haocheng Xu,
Jinliang Liu,
Lun Li
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2254/1/012017
Subject(s) - visual inspection , reliability (semiconductor) , reliability engineering , hot spot (computer programming) , sorting , computer science , thermal power station , power (physics) , automotive engineering , engineering , real time computing , artificial intelligence , electrical engineering , physics , quantum mechanics , programming language , operating system
Thermal power plant is a typical equipment-intensive enterprise, and regular inspection and spot inspection of production equipment is the most important measure to find equipment defects in time and ensure safe production of enterprises. In many years of practical application, the traditional inspection method, which relies mainly on visual inspection by spot inspectors, has been widely used. There are many shortcomings, such as missing detection, low efficiency, insufficient depth of data mining and high security risk. Based on the equipment management mode of spot inspection and regular maintenance in power plants, this paper proposes an unmanned intelligent spot inspection system for power plants, which combines intelligent sensors with diagnostic algorithms, by sorting out the work content of traditional manual spot inspection. The intelligent and unmanned management of spot inspection and regular repair in thermal power plants is realized, which has certain reference significance for improving the operation reliability of power plants and reducing the safety risk of spot inspection personnel.