Real-Time Monitoring Method of Icing on Overhead Transmission Lines Based on Multi-Sensor Information Fusion

Abstract

Icing on overhead transmission lines can be more accurately and effectively monitored in real time through a method that integrates information from multiple sensors for data fusion. SHT75 temperature and humidity sensor and ice thickness sensor are used to collect three kinds of sensing information of environmental temperature, humidity and ice thickness of transmission lines, and then input them into the ice fusion monitoring structure based on BP neural network. The weights and thresholds of a BP neural network can be optimized using a genetic algorithm, and fusion diagnosis is performed to determine if there is icing on transmission lines. For transmission lines with icing, by employing a fuzzy control-based evaluation method for line icing levels, the proposed approach enables the real-time assessment of icing levels on overhead transmission lines. Experimental findings demonstrate the method’s efficacy in swiftly and accurately detecting icing occurrences, thereby enhancing the precision and immediacy of icing monitoring on overhead transmission lines.

Keywords

• Multi-sensor
• information fusion
• overhead transmission lines
• real-time monitoring of icing
• temperature and humidity
• icing thickness