Steel material microstructure automatic identification method based on deep learning

A technology of microstructure and steel materials, applied in machine learning, character and pattern recognition, instruments, etc., can solve problems such as large errors, low efficiency of manual classification, and high dependence on manual analysis.

Active Publication Date: 2019-12-27
WUHAN UNIV OF SCI & TECH
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Problems solved by technology

Manual analysis is highly dependent on the level of professional knowledge and practical experience of technicians, and due to different pro

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  • Steel material microstructure automatic identification method based on deep learning
  • Steel material microstructure automatic identification method based on deep learning
  • Steel material microstructure automatic identification method based on deep learning

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Embodiment 1

[0041] The present invention is an automatic recognition method of steel microstructure based on deep learning, using advanced deep learning frameworks such as keras to build a convolutional neural network model, and using OpenCV (an open source computer vision library) to preprocess images.

[0042] Taking 120 10000× (i.e. magnified 10000 times) microstructure pictures of iron and steel materials taken by the historical experimental electron scanning microscope of the State Key Laboratory of Refractories and Metallurgy of Wuhan University of Science and Technology as an example, deep learning is used to analyze the microstructure of iron and steel materials. Automatic Identification.

[0043] The present invention is an automatic recognition method of steel microstructure based on deep learning, which is specifically carried out according to the following steps:

[0044] Step 1. Determine the type of steel microstructure to be identified and the microstructure magnification a...

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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...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N20/00G06K9/00
CPCG06N20/00G06V20/10G06N3/045G06F18/214Y02P90/30
Inventor 谌竟成李维刚赵云涛
Owner WUHAN UNIV OF SCI & TECH
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