计算机与数字工程2024，Vol.52Issue(5)：1587-1591,5.DOI:10.3969/j.issn.1672-9722.2024.05.056
基于多模型BP神经网络算法的湿化器的湿度预测控制
Humidity Predictive Control of Humidifier Based on Multi-model BP Neural Network Algorithm
苏健1
作者信息
- 1. 沈阳化工大学信息工程学院 沈阳 110000
- 折叠
摘要
Abstract
The humidity control effect of high-flow respiratory humidifier is an important standard to measure the quality of hu-midifier.Since humidity sensor is not used to collect data in real time at the air outlet of humidifier,the humidity of air-oxygen mix-ture at the air outlet of humidifier cannot be monitored in real time,so a complete closed-loop negative feedback system cannot be built.Only an open-loop system can be constructed with control based on estimated data.For humidity predictive control of humidifi-er,a BP neural network algorithm based on multi-model switching is proposed,which is linearized at the target temperature equilib-rium point,and the model is selected according to the change of flow rate.The experimental results show that the humidity predic-tive control system of humidifier has higher control quality and is suitable for different temperature and flow rate.关键词
湿化器/湿度预测/多模型/BP神经网络算法/线性化Key words
wet process/humidity prediction/multiple model/BP neural network algorithm/linearization分类
信息技术与安全科学引用本文复制引用
苏健..基于多模型BP神经网络算法的湿化器的湿度预测控制[J].计算机与数字工程,2024,52(5):1587-1591,5.
