基于人工鱼群BP神经网络算法的压力传感器温度补偿研究

Study on pressure sensor temperature compensation based on IAFSA-BP neural network algorithm

为实现压力传感器的温度补偿,采用BP神经网络作为压力传感器软件补偿系统的核心算法,但由于BP神经网络算法易陷入局部极值,因此采用具有全局搜索能力的算法—人工鱼群算法(AFSA)进行优化,得到的结果是压力传感器的线性度提升1个数量级,温度灵敏度系数降低2个数量级,得到了很好的补偿效果。

In order to achieve the temperature compensation of the pressure sensor,this paper adopts the BP neural network as the core algorithm of pressure sensor software compensation system,but as the result of the BP neural network algorithm is easily trapped in local minima,so it can be optimized by the algorithm with the global search ability-Artificial Fish Swarm Algorithm（ AFSA）. It improves the accuracy of measurement sensors.