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Research on High Reliability and Redundancy Design Method of Risk-driven Transformer Internal Inspection Robot

Yabiao Wang, Yuming Zhao, Xianshuai Sun, Zhen He, Zhigang Li

Year
2023
Citations
2

Abstract

Aiming at the demand for intelligent operation and maintenance of large-scale oil-immersed power transformers with high reliability tasks, the research on risk-driven design methods for power transformer internal inspection robots was carried out. From the perspective of operation and maintenance safety, we reduce the risks of robot operation and put forward a risk-driven robot system-wide high reliability and redundancy design method, which includes the robot structure design, control strategy, backup design and other dimensions. The research results of the article provide reliable theoretical support for the safe, reliable and intelligent operation and maintenance of power transformers, in the areas of robot space vector arrangement propulsion, omni-directional environment sensing vision, high reliability robot control strategy, and redundancy and hot backup system design. The research results of the article provide reliable theoretical support for safe and reliable intelligent operation and maintenance of power transformers.

Keywords

BackupReliability engineeringRobotRedundancy (engineering)TransformerMaintenance engineeringComputer scienceEngineeringControl engineeringArtificial intelligence

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