Monitoring Wind Turbine Blade Using Interferometric Radar

The use of interferometric radar to track subsidence and wind turbine blade deformation has been examined in a number of studies. This technology has two main advantages over other nondestructive surveying methods: the ability to quickly conduct network-level surveys, and the supply of time-series evidence of displacements via multitemporal data gathering. In order to address the drawbacks of convolutional neural networks (CNNs), such as network resemblance to the linear neuron model, operational neural networks (ONNs) have recently been developed. In this study, we present the results of employing ONNs in interferometry monitoring to assess a wind turbine’s structural health.