基于BP神经网络的钢铁分选仪裂纹检测 |
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引用本文: | 郝晓红,洪国铭.基于BP神经网络的钢铁分选仪裂纹检测[J].齐齐哈尔轻工业学院学报,2009(3):49-52. |
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作者姓名: | 郝晓红 洪国铭 |
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作者单位: | 哈尔滨理工大学,哈尔滨150080 |
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摘 要: | 将BP神经网络技术用于钢铁件缺陷分析,以钢铁件裂纹为研究对象,选取了8种影响裂纹的因素,在实验设计的基础上,用BP人工神经网络对所得实验结果进行了分析,并且用图形化方式直观地表达了出来。根据实验结果,BP神经网络模型能较准确地预测出钢铁缺陷,从而为研究裂纹检测提供了一种新的有效手段。
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关 键 词: | 钢铁件 裂纹 BP神经网络 |
Separation of steel based on BP neural network crack-detection |
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Authors: | HAO Xiao-hong HONG Guo-ming |
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Affiliation: | (Harbin University of Science and Technology, Harbin 150080, China) |
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Abstract: | BP neural network technology will be used for defect analysis of iron and steel pieces to study the crack of iron and steel pieces, the eight kinds of impact on the composition of crack were selected, on the basis of experimental design, BP artificial neural network analyzed the experimental results, and expressed the experimental results by intuitive graphical way, According to the experimental results, BP neural network model can predict steel deficiencies more accurately, so as to detect cracks study provides a new way of thinking and effective means. |
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Keywords: | crack BP Neural Networks Iron and steel pieces |
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