后缘
声学
噪音(视频)
空气声学
地质学
涡轮机
涡轮叶片
航空航天工程
物理
结构工程
工程类
计算机科学
声压
图像(数学)
人工智能
作者
Yang Zhang,Maciej Radzieński,Sidney Xue,Ziping Wang,Wiesław Ostachowicz
标识
DOI:10.1177/14759217241303452
摘要
This study uses aeroacoustic noise to identify cracking and debonding faults on the trailing edge (TE) of wind turbine blades, which is very meaningful because it can monitor early faults without affecting the normal operation of the wind turbine, thereby improving the safety and reliability of the wind turbines and extending the service life of the blades. First, the semi-empirical model called NAFNOISE is used to analyze the factors that influence the noise from the TE, such as chord length, angle of attack, and TE thickness. Computational aeroacoustics (CAA) as a more precise finite element method is further employed to calculate the areoacoustics noise (AAN) of the blade with TE cracking. Based on the vortex shedding diagram of the calculation results, a preliminary explanation is provided for the main reason high-frequency energy appears in the sound power spectrum when the blades have a TE cracking failure. Next, the semi-empirical model is compared with the noise waveforms obtained by CAA, the differences between different models in identifying TE cracking are analyzed, and the theoretical acoustic characteristics of AAN changes when blades fail are drawn. Finally, a noise detection experiment and corresponding signal processing technology are discussed. The results demonstrate that the method proposed in this article is not only capable of detecting debonding and cracking faults at the TE but also improves the theoretical research on active and noncontact damage monitoring of the blades.
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