Ingenium Research Group proposes a novel approach analyzing the noise waves in wind turbine fault detection. A novel condition monitoring system formed by an acoustic acquisition system embedded in a drone and connected to a ground station is developed for acoustic inspection. The noise present several sources, such as wind, wind turbine noise or the drone noise. Wavelet transform is employed for filtering and signal analysis. It leads classify, identify and study the different noises sources.
Our group has developed several experiments in a test rig simulation the real conditions of aerial acoustic inspection of the drone noise and machinery. The noise collected in the test rig is analysed by pattern recognition for fault detection and diagnosis. The results are studied by qualitative and quantitative analysis, obtaining different patterns for fault characterization with high accuracy.
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