Computer vision detection of mold breakout in slab continuous casting using an optimized neural network

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• 作者：Yu Liu ; Xudong Wang ; Fengming Du ; Man Yao…
• 关键词：Computer vision ; Mold breakout ; BP neural network ; Continuous casting
• 刊名：The International Journal of Advanced Manufacturing Technology
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：88
• 期：1-4
• 页码：557-564
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design;
• 出版者：Springer London
• ISSN：1433-3015
• 卷排序：88

文摘

A visual breakout prediction method for mold monitoring is proposed based on temperatures measured by thermocouples in the mold combined with the use of computer vision technology. This mold temperature rate thermography allows the characteristics of abnormal temperature regions to be captured and extracted, including the rate of temperature change with time, the geometry, and propagation velocity. On the basis of these characteristics, a back-propagation (BP) neural network model is constructed to detect mold breakout. The weight and threshold values of the model are optimized using the Levenberg–Marquardt (LM) algorithm and a genetic algorithm (GA) through an iterative process of sample training and testing. The results show that the GA–LM–BP neural network model is better than both the traditional BP and the LM–BP models. This breakout prediction model has a higher accuracy rate (83.3 %) and a lower false-alarm rate (0.05 %). The GA–LM–BP model has also been compared with an actual BOPS used in continuous casting production. Meanwhile, it provides a way of detecting abnormalities visually for continuous casting process. The results of this work also provide a positive example of the application of intelligent monitoring and visualization methods to continuous casting.