Abstract: The present invention provides an on-line real-time diagnosis system and method for wind turbine blade (WTB) damage. The system includes a four-rotor unmanned aerial vehicle (UAV), a cloud database, and a computer system. The four-rotor UAV captures images of WTBs in real time, and transmits the images to the computer system. The cloud database stores an image library used for a Visual Geometry Group (VGG)-19 net image classification method, where an image in the image library stored in the cloud database is dynamically captured from a network. The computer system is used to perform training by using the image library to obtain an improved VGG-19 net image classification method, and classify, by using the improved VGG-19 net image classification method, the images of the WTBs received from the four-rotor UAV, to obtain a WTB damage diagnosis and classification result and a damage grading result.

Abstract: The present invention provides an on-line real-time diagnosis system and method for wind turbine blade (WTB) damage. The system includes a four-rotor unmanned aerial vehicle (UAV), a cloud database, and a computer system. The four-rotor UAV captures images of WTBs in real time, and transmits the images to the computer system. The cloud database stores an image library used for a Visual Geometry Group (VGG)-19 net image classification method, where an image in the image library stored in the cloud database is dynamically captured from a network. The computer system is used to perform training by using the image library to obtain an improved VGG-19 net image classification method, and classify, by using the improved VGG-19 net image classification method, the images of the WTBs received from the four-rotor UAV, to obtain a WTB damage diagnosis and classification result and a damage grading result.