摘要
针对石化产业中难以实时、精确测量空冷器p H值的问题,提出一种基于BP算法的神经网络模型,实现对空冷器的pH值进行软测量。通过现场采集的数据集,利用BP算法构建网络模型,调整训练参数和网络结构,找到效果最好的模型。测试结果表明,该方法预测精度高,测量方便,为实际生产参数测量提供了一种行之有效的思路。
In order to solve the problem of real time and accurate measurement of the pH value of air cooler,a neural network model is proposed in this paper.It is constructed by BP algorithm,and the training parameters and network structure are adjusted to find the best model.The test results show that the method has high prediction accuracy and convenient measurement.It provides an effective way to measure the practical industrial parameters.
出处
《工业控制计算机》
2018年第12期63-64,共2页
Industrial Control Computer
基金
浙江省自然科学基金(LY17F030024)
2017年国家级大学生创新创业训练计划项目(201710338006)
关键词
空冷器
软测量
BP算法
pH值建模
air cooler
soft sensor
BP neural network
modeling of pH value