Joint Inspection of HD Video and Robot in Substation Based on OCR Technology | Zendy

Xiao Liao | Zendy; Ke Xie | Zendy; Zhen Qiu | Zendy

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Joint Inspection of HD Video and Robot in Substation Based on OCR Technology

Author(s) -

Xiao Liao,

Ke Xie,

Zhen Qiu

Publication year - 2021

Publication title -

mobile information systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.346

H-Index - 34

eISSN - 1875-905X

pISSN - 1574-017X

DOI - 10.1155/2021/8088574

Subject(s) - computer science , robot , reliability (semiconductor) , visual inspection , joint (building) , artificial intelligence , identification (biology) , interface (matter) , construct (python library) , computer vision , component (thermodynamics) , real time computing , programming language , thermodynamics , architectural engineering , power (physics) , physics , botany , bubble , quantum mechanics , maximum bubble pressure method , parallel computing , engineering , biology

The research on the joint inspection technology of HD video and robot in substation is of great significance in the operation and maintenance management of substation. The related research on multidimensional collaborative inspection technology of substation has attracted great attention. The substation monitoring system is designed to realize multidimensional collaborative inspection of HD video and inspection robot. OCR technology is used to improve the abnormal recognition system of inspection robot equipment. According to the collection of video information, DSP comprehensive information processing is carried out, and the detection information is analyzed by frequency domain filtering method through human-computer interaction interface. Meanwhile, the main component features of substation detection components are extracted by pattern recognition method, and the resolution model of similar features of video monitoring images is constructed. It plays an important role in the daily operation and maintenance of substation to construct the reliability visual tracking and identification model and optimize the multidimensional cooperative inspection system model.

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