Steel material microstructure automatic identification method based on deep learning

Abstract

The invention discloses a steel material microstructure automatic identification method based on deep learning. The method comprises the following steps: 1, determining the microstructure type and microstructure magnification times of to-be-identified steel, collecting historical steel material microstructure pictures with the same specification and size obtained by an electronic scanning microscope under the magnification times to obtain a data set, and determining a category label for each picture in the data set; 2, performing the same preprocessing on all the pictures collected in the step1; 3, constructing a convolutional neural network CNN-ICAM model; 4, presetting the number of iterations, using cross entropy as a loss function, and training a neural network CNN-ICAM model by usinga stochastic gradient descent method; and 5, preprocessing a steel material microstructure picture to be recognized according to the method in the step 2, and then automatically recognizing the steelmaterial microstructure picture by using the convolutional neural network model trained in the step 4. The method not only can improve the identification precision, but also can improve the recognition speed.

Description

technical field [0001] The invention belongs to the technical field of microstructure identification of iron and steel materials, and relates to an automatic identification method of microstructure of iron and steel materials based on deep learning, in particular to an automatic identification method of microstructure of iron and steel materials based on convolutional neural network. Background technique [0002] With its excellent mechanical properties and low cost, steel is still one of the most important and widely used materials. The microstructure of steel is rich and diverse, including ferrite, pearlite, bainite, martensite, austenite Its microstructure type, content, size, shape and distribution determine the properties of the material, so it is of great significance to study the microstructure of steel materials. [0003] In the microstructure of iron and steel materials, how to correctly classify the microstructure is particularly important. Affected by heating con...

AI Technical Summary

Problems solved by technology

Manual analysis is highly dependent on the level of professional knowledge and practical experience of technicians, and due to different professional levels of technicians, different opinions will be generated, which makes manual classification less efficient and more error-prone

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