Wireless Radio Frequency Monitoring Trend Forecast of Internet of Things for Wind Turbines Based on Energy Decoupling Algorithm


  • Xiaojing Wan , Wenlei Sun , Kun Chen , Xiaodong Zhang


With the increasingly strict environmental protection, the renewable energy represented
by wind power generation has received increasing attention. However, the installation
location of wind power generators is relatively remote, and the natural environment is
relatively harsh. In addition, due to the influence of power electronic devices such as
inverters and power grid harmonics, it is prone to breaking down. In this paper, an
algorithm for predicting the operating trends of wind power rotating machinery based on
the energy decoupling is put forward to achieve the extraction of the operating trend
characteristics of the key components in the equipment group. The Hadoop cloud
computing technology is used to meet the needs of reliable storage and effective
management of massive data for wind power generation. In addition, the ZigBee
technology, Internet of Things (IoT) technology, and wireless sensor network
technology are used to perform the real-time remote data acquisition of wind power
generation equipment. The practice shows that the proposed method is feasible, which
can effectively reduce the storage and computing equipment of intelligent monitoring
equipment, implement intelligent remote monitoring, and facilitate the intelligent
management of wind power generation