首页|Reports Summarize Artificial Intelligence Study Results from National Taiwan University of Science and Technology (Real-Time Salt Contamination Monitoring System and Method for Transmission Line Insulator Based on Artificial Intelligence)

Reports Summarize Artificial Intelligence Study Results from National Taiwan University of Science and Technology (Real-Time Salt Contamination Monitoring System and Method for Transmission Line Insulator Based on Artificial Intelligence)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intelligence are discussed in a new report. According to news originating from Taipei, Taiwan, by NewsRx correspondents, research stated, "Insulators on overhead power lines have long been exposed to the outdoors and are susceptible to pollution and salt contamination. Due to factors such as wind and gravity, pollution in the atmosphere gradually deposits on the surface of the insulator." The news journalists obtained a quote from the research from National Taiwan University of Science and Technology: "In humid and windy conditions, conductive pollutants begin to dissolve in the water on the surface of the insulator, increasing the leakage current and affecting insulation performance. This study mainly uses a data acquisition system to measure the leakage current of the insulator and weather parameters (including temperature, relative humidity, pressure, wind speed, and ultraviolet) around the insulator. Artificial intelligence is then applied to establish a prediction model for leakage current based on weather parameters. The established model accurately predicts insulator leakage current through weather parameters. In order to observe the real-time status of the insulator, this study establishes a monitoring platform that integrates the predicted leakage current with weather parameters. It allows users or maintenance personnel to connect to the server through the network to observe the predicted results and weather parameters."

National Taiwan University of Science and TechnologyTaipeiTaiwanAsiaArtificial IntelligenceEmerging TechnologiesMachine Learning

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Mar.5)