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Metals 2017, 7(8), 311; doi:10.3390/met7080311

An Algorithm for Surface Defect Identification of Steel Plates Based on Genetic Algorithm and Extreme Learning Machine

1
and
2,*
1
National Engineering Research Center of Advanced Rolling Technology, University of Science and Technology Beijing, Beijing 100083, China
2
Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Received: 30 June 2017 / Revised: 5 August 2017 / Accepted: 8 August 2017 / Published: 15 August 2017
(This article belongs to the Special Issue Researches and Simulations in Steel Rolling)
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Abstract

Defects on the surface of steel plates are one of the most important factors affecting the quality of steel plates. It is of great importance to detect such defects through online surface inspection systems, whose ability of defect identification comes from self-learning through training samples. Extreme Learning Machine (ELM) is a fast machine learning algorithm with a high accuracy of identification. ELM is implemented by a hidden matrix generated with random initialization parameters, while different parameters usually result in different performances. To solve this problem, an improved ELM algorithm combined with a Genetic Algorithm was proposed and applied for the surface defect identification of hot rolled steel plates. The output matrix of the ELM’s hidden layers was treated as a chromosome, and some novel iteration rules were added. The algorithm was tested with 1675 samples of hot rolled steel plates, including pockmarks, chaps, scars, longitudinal cracks, longitudinal scratches, scales, transverse cracks, transverse scratches, and roll marks. The results showed that the highest identification accuracies for the training and the testing set obtained by the G-ELM (Genetic Extreme Learning Machine) algorithm were 98.46% and 94.30%, respectively, which were about 5% higher than those obtained by the ELM algorithm. View Full-Text
Keywords: surface inspection; steel plate; genetic algorithm; ELM surface inspection; steel plate; genetic algorithm; ELM
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Tian, S.; Xu, K. An Algorithm for Surface Defect Identification of Steel Plates Based on Genetic Algorithm and Extreme Learning Machine. Metals 2017, 7, 311.

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