基于混合优化算法的压力传感器温度补偿

针对压阻式压力传感器存在温度漂移,其测量精度受温度影响很大的问题,使用最小二乘拟合方法与RBF神经网络共同建立压力传感器温度补偿模型.针对低温和高温区域使用RBF神经网络进行补偿,对中间线性区域使用最小二乘拟合方法进行补偿.同时为了提高RBF神经网络拟合效果,使用进化算法和下降梯度算法优化RBF神经网络参数.实验结果表明,本文使用方法与单纯使用RBF神经网络或最小二乘拟合方法进行温度补偿,具有更高的训练效率和温度补偿效果,能够提高压力传感器在各种环境下的测量精度和工作可靠性.

Temperature compensation of pressure sensor based on hybrid optimization algorithm

Aiming at the temperature drift of the pressure resistance sensor,the measurement accuracy is greatly af?fected by the temperature,and the temperature compensation model of pressure sensor is established by using the least square fitting method and the RBF neural network. The RBF neural network is used to compensate the low tem?perature and high temperature region,and the least square fitting method is used to compensate the middle linear re?gion. At the same time in order to improve the RBF neural network fitting effect,using the evolutionary algorithm and the descent gradient algorithm to optimize the RBF neural network parameters. Experimental results show that the use method and simple use of RBF neural network and least square fitting method for temperature compensa?tion,has higher training efficiency and effect of temperature compensation,can improve the pressure sensor under various environmental measurement precision and reliability.