Automatic Discontinuity Classification of Wind-Turbine Blades using A-Scan-Based Convolutional Neural Network - SGEPRI Journals & Magazine
Recent development trends in wind power generation have increased the importance of the safe operation of wind-turbine blades (WTBs). To realize this objective, it is essential to inspect WTBs for any defects before they are placed into operation. However, conventional methods of fault inspection in WTBs can be rather difficult to implement, since complex curvatures that characterize the WTB structures must ensure accurate and reliable inspection. Moreover, it is considered useful if inspection results can be objectively and consistently classified and analyzed by an automated system and not by the subjective judgment of an inspector.....
