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| 摘要: |
| 利用热电偶测得的退火窑中空气温度和红外测温仪测得的玻璃表面温度作为训练样本,建立了基于BP神经网络的玻璃温度预测模型.通过与实际工况对比,证实了该模型的有效性.该模型对改善玻璃退火窑运行质量,预测玻璃成型性能具有积极的意义. |
| 关键词: BP神经网络,浮法玻璃,退火温度,退火窑 |
| DOI： |
| 分类号:TP183 TQ171.64 |
| 基金项目: |
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| Temperature Prediction for the Float Glass Ribbon in Lehr Based on BP Neural Network |
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ZHU Jin-jie TONG Shu-ting GUO Feng-Jiao
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| Abstract: |
| By using the air temperature measured by thermocouples and the glass temperature measured by infrared thermometer as the training sample , a model for prediction of the temperature parameters for the float glass in lehr was created based on the ameliorated BP neural network. The results of simulation show that the model is effective and feasible. It can improve the quality of the annealing process and diagnose some failures. |
| Key words: BP neural network,float glass,annealing temperature,lehr, |
