基于改进型ANFIS的磁致伸缩液位传感器温度补偿∗

摘要

Taking into account the temperature drift of the magnetostrictive liquid level sensor is serious in the large temperature difference,and it is difficult to use the mathematical model to express the nonlinear relation between temperature drift phenomenon and the variety of factors,establish a temperature compensation system based on im-proved ANFIS. This system uses the Additional momentum method to constantly modify premise parameters in AN-FIS in order to avoid the shortcomings that it easy to fall into local minimum point and slow training speed when u-sing the gradient descent algorithm,and improve the capacity of ignoring tiny changes in the network. In order to verify the performance of the temperature compensation system,it has been compared with other temperature com-pensation system based on PSO-LSSVM and BP neural network. Analysis and experimental results show that the maximum error and its mean error of improved ANFIS model is 0.88% and 0.65%,far less than the other two kinds of compensation methods. This temperature compensation system based on improved ANFIS has strong generalization ability and can effectively eliminate the influence by temperature on the magnetostrictive liquid level sensor.%考虑到磁致伸缩液位传感器在温差变化大的环境中温漂现象严重，且产生温漂的多种因素与温漂的程度呈非线性关系，难以用数学模型表达等问题，建立基于改进型ANFIS的温度补偿系统。该系统采用附加动量算法不断修正ANFIS中的前题参数以避免采用梯度下降算法时易陷入局部极小，训练速度较慢等缺点，提高系统的忽略网络中微小变化的能力。为了验证该温度补偿系统的性能，将其与基于PSO-LSSVM模型和基于BP神经网络的温度补偿系统相比较。分析与实验结果表明，改进型ANFIS模型的温度补偿的最大误差为0.88%，平均误差为0.65%，远小于另外两种补偿方法。使用了改进型ANFIS的温度补偿方法具有较强的泛化能力，能够有效消除温度对磁致伸缩液位传感器的影响。