Abstract
The main objective of presented research is an attempt of application of techniques taken from a dynamically developing field of image analysis based on Artificial Intelligence, particularly on Deep Learning, in classification of steel microstructures. Our research focused on developing and implementation of Deep Convolutional Neural Networks (DCNN) for classification of different types of steel microstructure photographs received from the light microscopy at the TU Bergakademie, Freiberg. First, brief presentation of the idea of the system based on DCNN is given. Next, the results of tests of developed classification system on 8 different types (classes) of microstructure of the following different steel grades: C15, C45, C60, C80, V33, X70 and carbide free steel. The DCNN based classification systems require numerous training data and the system accuracy strongly depend on the size of these data. Therefore, created data set of numerous micrograph images of different types of microstructure (33283 photographs) gave the opportunity to develop high precision classification systems and segmentation routines, reaching the accuracy of 99.8%. Presented results confirm, that DCNN can be a useful tool in microstructure classification.
Highlights
The effort of promoting light weight design in the wide spectrum of industry can be realized by application of new materials
The main goal of our research is to develop a system for microstructure image recognition based on the Artificial Neural Networks, on the Deep Learning
Nowadays big databases with a lot of examples are widely available, as it was in our case of the microstructure photographs. In this paragraph we briefly describe methods that were implemented in our Deep Convolutional Neural Networks (DCNN) approach and our learning algorithm
Summary
The effort of promoting light weight design in the wide spectrum of industry can be realized by application of new materials. There are two groups of materials which are being focused on by industry at the moment. One group consists of materials with a low density such as aluminum, magnesium or carbon fiber reinforced polymers, while the other group consists of high strength steels. The latter group includes multiphase steels which offer, besides high strength, a good forming ability. Another advantage of these steels can be found in the low alloy element content which often is below 5%, not leading to an increase of costs.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
