Transmission Line Safety Distance Measurement and Data Online Fusion Processing Technology Based on Multi Physical Quantity Sensing

To address the real-time monitoring challenges of mechanical collision prevention for power transmission lines, this paper developed a warning device based on multiple sensor sources and proposed a transmission line warning algorithm based on multisensor fusion. The effectiveness of the algorithm was validated in real-world scenarios. The warning device based on multiple sensor sources first employed a visual recognition algorithm based on standard deviation clustering to identify the transmission lines ahead. Subsequently, the millimeter-wave radar in the ranging module was connected to the detection host via a wired interface. The radar data input utilized a millimeter-wave radar ranging algorithm based on improved robust Kalman filtering, providing real-time output of distance and azimuthal information of the power transmission lines at a frequency of 1Hz Experimental results demonstrated that the visual recognition algorithm based on standard deviation clustering effectively identified distances greater than 20 meters with a recognition accuracy of 93% and an output frequency of IHz The millimeter-wave radar ranging algorithm, based on improved robust Kalman filtering, achieved a ranging accuracy of ±0.1m and a ranging error of 2%, operating at an output frequency of IHz These findings confirm that the system adequately meets the overall requirements for real-time monitoring of mechanical collision prevention for power transmission lines.