Scratch detection system of the inner surface of super long gas cylinder based on VGG-16 neural networks
by Baocheng He; Linguang Li; Shijie Ren; Dianwei Qian
International Journal of Advanced Mechatronic Systems (IJAMECHS), Vol. 9, No. 4, 2022

Abstract: Aiming at the problems of difficulty and low detection accuracy in manual detection of scratches on the inner surface of ultra-long energy storage gas cylinders in the aerospace industry, a detection system for scratches on the inner surface of ultra-long gas cylinders based on VGG-16 neural network is designed. In this paper, VGG-16 recognition model is innovatively proposed to apply to the application of scratch detection. Compared with the ordinary detection model to detect the required target from the complex background, this article first processes the image acquired by the image acquisition module into a single binary image with a scratched area and a non-scratched area. The VGG-16 recognition model learns the characteristics of the scratches, so as to recognise the scratches under the ordinary background, and achieve the purpose of scratch detection. The results show that the accuracy rate of the scratch detection on the inner surface of gas cylinders reaches 98.5%, which greatly improves the accuracy rate of the scratch detection compared with the previous manual detection methods.

Online publication date: Tue, 31-May-2022

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