基于统计分析的温度控制系统改进研究

Research on Improvement of Temperature Control System Based on Statistical Analysis

在常用设备的温度控制系统中,温度传感器主要有两类,即数字型和模拟型。模拟型传感器因成本低、体积小而被大规模使用,但是其在使用时需要做数据、算法的处理。本文针对传统算法中线性回归的理论弊端,提出基于统计科学的控制方法,先对模型的数据分析进行改进并结合控制模型计算出95%的置信区间,然后计算出整个温区的预测区间。与传统的线性回归算法相比,基于统计分析的温度控制系统改进方法得到的温度更加准确,精度更高。

In the temperature control system of commonly used equipment,there are two main types of temperature sensors,namely digital and analog.Analog sensors are used on a large scale due to their low cost and small size,but they require data and algorithm processing when they are used.Aiming at the theoretical disadvantages of linear regression in traditional algorithms,this paper proposed a control method based on statistical science,firstly improved the data analysis of the model and calculated the 95%confidence interval in combination with the control model,and then calculated the prediction interval of the entire temperature zone.Compared with the traditional linear regression algorithm,the temperature obtained by the improved method of temperature control system based on statistical analysis is more accurate and more accurate.