Unsupervised enhancement method for surface defect image data of hot-rolled plate coil

Abstract

The invention discloses an unsupervised enhancement method for hot-rolled plate coil surface defect image data, and belongs to the technical field of metallurgical hot-rolled plate coil defect detection. The generative adversarial network is composed of two deep neural networks with mutual adversarial competition and is a probability generation model, forward propagation is carried out on a samplegeneration mode through a generator, gradient back propagation is used for carrying out optimization calculation after discrimination is carried out through a discriminator, and the method does not depend on any prior hypothesis. In the training process of the productive adversarial network, the two networks are continuously iterated and optimized in the mutual game, the generator learns and generates a more real sample, and the discrimination network discriminates whether a data sample is a real sample or a generated false sample as much as possible. The two parties continuously compete until the last two parties cannot become better, and finally, the two networks achieve a dynamic balance, i.e., the distribution of the images generated by the generator is close to the distribution of real images, and the discriminator cannot identify true and false images. The method has the advantage of solving the problems of few hot-rolled plate coil surface defect picture data, difficulty in collection, low recognition accuracy and the like in the metallurgical steel rolling field.

Description

technical field [0001] The invention belongs to the technical field of defect detection of metallurgical hot-rolled coils, and relates to a method for generating image data of surface defects of hot-rolled coils based on an artificial intelligence network model. Background technique [0002] In the era of continuous industrial development, steel can be said to be the "food" of industry, and it is one of the most important materials in modern times. However, in the process of actually producing steel plates and coils in steel mills, due to the influence of factors such as equipment problems and processing techniques, hot-rolled coils with surface defects are often produced. If the surface defects of the coil cannot be detected and identified effectively, it will seriously affect its quality as a steel product, its appearance, economic benefits, performance, etc., so the research on the defect identification of the coil surface has great practical significance. Early defect d...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a method that can stably and effectively generate image data of surface defects of hot-rolled coils, so as to solve the problem that the data of surface defects of hot-rolled coils in the field of metallurgical rolling are scarce and difficult to obtain, which leads to the use of artificial intelligence machine vision technology to identify The accuracy of defects is low, which seriously affects the quality of its products

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