About the author:

Xinjiang Branch of PowerChina Renewable Energy Co., Ltd., Urumqi, Xinjiang 830000, China

Abstract:

Wind turbine hoisting is a critical phase in wind power project construction. Traditionalhoisting management relies heavily on manual experience, which poses significant safety risks andefficiency limitations. To enhance the intelligence level of hoisting operations, this paper designs andimplements a smart monitoring and early warning system covering the entire hoisting process. Byintegrating multi⁃source sensing data, such as wind speed, hoisting angle, and equipment status, withartificial intelligence and big data analytics, the system enables real⁃time monitoring, risk forecasting,and intelligent decision support. The system has been deployed in the wind power project in TuokexunCounty, yielding notable results in improving operational safety, construction efficiency, and on⁃sitemanagement. Additionally, the system incorporates an embedded UAV inspection module, breaking awayfrom traditional management models and enhancing information flow and decision responsiveness on theconstruction site. This paper presents the application outcomes of the system in wind power projects anddiscusses prospects for the future development of intelligent construction technologies in the wind energysector.