Xiaodan Cong

Papers

Total Citations

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About

Xiaodan Cong is a researcher specializing in intelligent inspection systems, sensor-based measurement, and autonomous robotics for infrastructure monitoring. Their work focuses on developing innovative solutions for detecting and maintaining critical components in energy and pipeline systems. Cong’s most-cited paper, "Junction Detection Based on CCWT and MEMS Accelerometer Measurement" (2018, 4 citations), introduces a novel method for identifying pipeline junctions using continuous complex wavelet transform and micro-electromechanical system accelerometers, enabling precise navigation of pipeline inspection gauges. A more recent contribution, "Intelligent Inspection and Deicing System for Power Transmission Lines Based on UAV Platform" (2025, 2 citations), addresses the pressing challenge of ice accumulation on power lines by proposing an integrated unmanned aerial vehicle solution for both inspection and deicing, enhancing safety and efficiency over traditional manual methods. Cong’s work bridges sensor technology and autonomous platforms, offering practical, high-precision tools for real-world infrastructure challenges. With a focus on reducing human risk and operational costs, their research holds significant promise for the future of smart energy and pipeline maintenance.