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Research on Application of Location Technology in 3D Virtual Environment Modeling System for Substation Switch Indicator

By Qin LJ(秦丽娟), Wang T(王挺) and Yao C(姚辰)

Abstract

Substation inspection work plays a very important role in ensuring the normal production and the safe operation of a transformer substation. Use of a substation inspection robot can effectively solve the omission problems of a manual inspection. It can further improve the unmanned and automation of substation and improve security of station. A substation inspection system requires the establishment of a spatial position relation between the robot and the inspection object in the monitoring station. Key technology is the spatial location of the object being detected in the substation. The position of inspection object is unknown. This paper gives technical route of monocular vision positioning system based on switch indicator sign cooperative target. The knife switch indicator is one of the most important objects in the substation inspection. Usually the switch indicator lies in the middle or top of the substation equipment and conventional method can't measure. This paper presents a substation label measurement method based on monocular vision. In this method, the label frame of knife switch indicator is as a cooperative target. The 3D coordinates and attitude of the label frame can be calculated in a camera coordinates system. At the same time, this paper introduces an extraction process of knife brake indicator label with multi-features under complex background. At last, we do simulation experiment for positioning technology of 3D virtual environment modeling system for substation switch indicator. Simulation results show that the method introduced in this paper can realize positioning of substation switch indicator label

Topics: Substation, Switch indicator, 3D virtual environment modeling system, Location technology, Automation & Control Systems, Computer Science, Artificial Intelligence, Automation & Control Systems, Computer Science
Year: 2018
OAI identifier: oai:ir.sia.cn/:173321/22779
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