Xinyang Zhao

Papers

Total Citations

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About

Xinyang Zhao is a robotics engineer specializing in intelligent inspection systems for electric power infrastructure. His primary research focuses on the structural design, control systems, and automation of indoor rail inspection robots for substations, with particular emphasis on enhancing precision and operational reliability. Zhao’s most influential work, “Structure Design and Application of Combination Track Intelligent Inspection Robot Used in Substation Indoor” (2017, 19 citations), introduces a novel combined-track robot architecture that integrates linear planning algorithms to navigate complex indoor substation environments. This contribution addresses critical challenges in automating equipment monitoring, reducing human intervention while improving inspection consistency. In a complementary study, “PTZ Control System of Indoor Rail Inspection Robot Based on Neural Network Prediction Model” (2017, 6 citations), Zhao advances pan-tilt-zoom (PTZ) accuracy using neural network predictive control, directly impacting the quality of visual data collection during autonomous patrols. His work bridges mechanical design and intelligent control, laying foundational methods for modern substation automation. Zhao’s research is particularly relevant for engineers developing reliable, low-maintenance inspection solutions in high-stakes industrial settings, and his citation record reflects growing interest in robotics for critical infrastructure monitoring.