Tempering color classification via artificial neural network (ANN): An intelligent system approach to steel thermography

College

Gokongwei College of Engineering

Department/Unit

Manufacturing Engineering and Management

Document Type

Conference Proceeding

Source Title

2017 International Conference on Electrical, Electronics and System Engineering, ICEESE 2017

Volume

2018-January

First Page

84

Last Page

88

Publication Date

2-20-2018

Abstract

In our modern society, the steel industry is a critical component to achieve economic growth and development especially in the infrastructure and manufacturing industries. However, steel production is not just an easy step process. Untempered steel, though hard, is too brittle to be useful for most applications. In order to enhance its properties, the application of heat treatment is performed to steel. Heat treatment is a meticulously sensitive and an extremely tedious process due to temperature sensing. Nowadays, the common way to determine the temperature of a certain metal is through the use of human vision or a thermal imaging camera. However, these methods are either inaccurate or very expensive to setup. In this study, the application of artificial neural networks (ANN) in assessing the steel discoloration when it undergoes extreme temperatures is a cheaper and more accurate way of reading or sensing its temperature. The use of neural network technology can easily adapt to classify a wide range of discoloration from different metals especially steel. © 2017 IEEE.

html

Digitial Object Identifier (DOI)

10.1109/ICEESE.2017.8298387

Disciplines

Manufacturing

Keywords

Steel—Heating; Neural networks (Computer science)

Upload File

wf_no

This document is currently not available here.

Share

COinS