摘要
针对纺织浆纱生产中,产品规格、原料状况和工况环境等难以实现操作参数的优化设定问题,提出了基于数据模型的操作参数设定方法.利用已有的生产操作参数及上浆率数据建立浆纱上浆率预测模型,将上浆率指标作为输入,操作参数作为输出建立神经网络逆模型.通过该神经网络逆模型计算出满足期望上浆率指标的操作变量设定值,并利用上浆率预测模型验证所计算出的操作变量设定值.实验结果表明,所提出的基于数据模型的操作参数设定方法是有效的.
The operating parameter setting method based on data model was proposed for textile slashing process where the operating parameter optimization setting is difficult to be realized for various production specifications, material states and operating conditions. The size add-on prediction model was established by the known operating parameters and size add-on data. An inverse neural network model was established where the size add-on was taken as the input variable and the operating parameter was chosen as the output variable. The operating parameter setting values to satisfy the desired size add-on were calculated by the inverse neural network model, and the calculated operating parameter setting values were verified by the size add-on prediction model. The results show that the proposed operating parameter setting method based on data model is effective.
出处
《沈阳工业大学学报》
EI
CAS
2011年第3期303-307,共5页
Journal of Shenyang University of Technology
基金
国家自然科学基金资助项目(50805098)
关键词
操作参数设定
数据建模
预测模型
神经网络
逆模型
浆纱过程
期望指标
上浆率
operating parameter setting
data modeling
prediction model
neural network
inverse model
slashing process
desired index
size add-on
