Jian Fang
Papers
1
Total Citations
2
H-Index
1
About
Jian Fang’s research centers on intelligent inspection systems for electrical equipment, with a focus on robotic automation and signal processing for switchgear safety. His key contribution is a real-time inspection method for verifying the compliance of circuit breaker trolleys in switchgear, detailed in his 2021 paper. This work proposes a wavelet transform algorithm integrated with Kalman filtering to analyze torque signals from a robot during inspection. By windowing the filtered data and applying wavelet decomposition and reconstruction, the method enables precise, real-time detection of mechanical anomalies, enhancing the reliability of high-voltage equipment. While his most-cited paper has 2 citations, reflecting a specialized niche, the work addresses a critical gap in automated power system maintenance—combining robotics with advanced signal analysis to reduce human error and downtime. Fang’s approach exemplifies how practical engineering challenges can be solved through cross-disciplinary techniques, making his research valuable for students and engineers in industrial automation and electrical safety. His focus on real-time, robot-driven inspection aligns with broader trends toward smart grid and predictive maintenance technologies.
Research Focus
Key Achievements
Top Papers
- 1