信息与控制2017，Vol.46Issue(3)：328-334,7.DOI:10.13976/j.cnki.xk.2017.0328
模压时效炉锻件温度软测量方法
Temperature Soft Sensor Method for Molded Aging Ovens
摘要
Abstract
The forging temperature of a molded aging oven is difficult to measure directly.Thus, we build a temperature soft measurement model based on mixed kernel partial least squares algorithm (KPLS).The model estimates the actual forging temperature by collecting the furnace wall temperature, which is easy to obtain.To improve the accuracy of the model, we apply a local weighting algorithm to determine the weights of the training samples.Experimental results show that the soft measurement model of local weighted mixed-kernel partial least squares (LWKPLS) has better adaptability to data and meets the requirements of actual temperature prediction accuracy.It solves the quality problems of aluminum alloy products under oven burning temperature, thereby providing the basis for optimization control of the production process.关键词
时效炉/温度软测量/核偏最小二乘/混合核函数Key words
aging oven/temperature soft sensor/partial least squares algorithm/mixed kernel function分类
信息技术与安全科学引用本文复制引用
于清,贺建军..模压时效炉锻件温度软测量方法[J].信息与控制,2017,46(3):328-334,7.基金项目
国家自然科学基金资助项目(61174132) （61174132）
高等学校博士学科点专项科研基金资助项目(20130162110067) （20130162110067）
