| 基于机器视觉和神经网络的烧结质量预测 |
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| 引用本文： | 孙铁强,尹怡欣,董洁,涂序彦. 基于机器视觉和神经网络的烧结质量预测[J]. 计算机工程, 2008, 34(11): 240-242 |
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| 作者姓名： | 孙铁强 尹怡欣 董洁 涂序彦 |
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| 作者单位： | 1. 河北理工大学信息学院,唐山,063009;北京科技大学信息工程学院,北京,100083
2. 北京科技大学信息工程学院,北京,100083 |
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| 摘 要： | 应用机器视觉和人工神经网络理论提出了对烧结质量在线判断的一种模式识别方法。以某烧结厂为研究背景，分析影响烧结质量的视觉特征，从烧结机机尾摄取断面图像并进行处理，用图像的空间低阶矩描述目标的视觉特征，从而可以选出对分类识别最有效的特征作为人工神经网络的输入，构造改进的BP神经网络分类器，实现在线判断烧结质量，实验证明了该方法有效可行。
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| 关 键 词： | 视觉特征 图像处理 烧结 人工神经网络 |
| 文章编号： | 1000-3428(2008)11-0240-03 |
| 修稿时间： | 2007-06-19 |
Sintering Quality Prediction Based on Machine Vision and ANN |
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| SUN Tie-qiang,YIN Yi-xin,DONG Jie,TU Xu-yan. Sintering Quality Prediction Based on Machine Vision and ANN[J]. Computer Engineering, 2008, 34(11): 240-242 |
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| Authors: | SUN Tie-qiang YIN Yi-xin DONG Jie TU Xu-yan |
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| Affiliation: | (1. College of Information, Hebei Polytechenic University, Tangshang 063009; 2. School of Information Engineering, University of Science and Technology Beijing, Beijing 100083) |
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| Abstract: | According to the theory of machine vision and ANN, a pattern recognition method for online prediction of sintering quality is put forward. Based on some sintering plant, the vision characteristics which affect sintering quality are analyzed. And the images of sintering at the end of the sintering machine are processed. Images’ spatial lower order moments are used to describe those vision characteristics. As a result, most effective characteristics for classification and recognition are selected as the input of ANN. An improved BP classifier is proposed to realize sintering quality online prediction as well. Experimental result shows that the proposed method is feasible. |
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| Keywords: | vision characteristic image processing sintering ANN |
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