Active Icing Monitoring For A Wind Turbine Blade Model With PZT Technology

With the rapid growth in world‘s economy, the amount of energy assumption is also increasing. Putting forward an reliable and effective solution to this problem is in urgent need. Wind power has its global reputation as a kind of clean and renewable energy. It has become one of the most prospective energy solution in this new century. With the rapid development of wind farms construction, some problems have to be solved. For example, the harsh environment with low temperature and high humidity in mountain area of south region easily leads to ice hazard. Ice on the wind turbine blade can deteriorate power generating efficiency and even lead to generator shu tdown. The development of efficient ice monitoring methodology is critical for a nti-icing and de-icing. In this study, an active icing monitoring approach based on stress wave propagation method for a wind turbine bl ade model using piezoelectric ceramic(PZT) is proposed.The specific study is listed as follows:(1)The fabrication of the employed axial compressive and shear type piezoele ctric transdusers are introduced in detail and their static and dynamic performance s are studied and calibrated by the following sine excitation signal test.(2)Three identical pieces of FRP blade model of one meter long is fabricated in the lab. Install all the piezoelectric sensors at the specified positions, based on wave propagation method, various working conditions is designed for PZT sensors in order to identify different types of state.(3)Experimental study on the blade model covered with different thicknesses of ice is carried out. The corresponding voltage responses of different sensors are recorded when a certain designated actuator was excited with sine sweeping signals.(4)Introduced the basic theory of wavelet packet energy. The wavelet packet analysis is conducted on the received signals and the corresponding wavel et packet energy are investigated. The results show that the wavelet packet energy of the vol tage signals of the PZT patch is obviously related to the ice thickness. The proposed method can be adopted as a novel monitoring approach for the icing conditions detection of wind turbine blade and is applicable in practice.