基于改进灰色模型预测的节流流量传感器测量校正方法

Throttle flow sensor measurement and correction method based on improved grey model prediction

为了提高节流流量传感器的测量校正精度,提出一种基于改进灰色GM(1,1)模型的预测校正方法。该方法首先对灰色GM(1,1)模型的流程进行改进,并采用LM方法对GM(1,1)模型的初始值进行求解计算;然后利用基于Markov过程的残差修正模型进一步提高预测精度;最后通过实例分析验证了提出方法的可行性。实验结果表明,相比传统灰色GM(1,1)模型,提出改进模型的预测值与实际测量值的拟合度更好,有效降低了校正后的节流流量传感器的测量误差。

A prediction correction method based on the improved gray model GM(1,1)is proposed to improve the measure.ment correction accuracy of the throttle flow sensor.The flow of the GM(1,1)model is improved by the proposed method,and the least square(LM)method is used to solve the initial value of the GM(1,1)model.The residual error modification model based on Markov process is adopted to further improve the prediction accuracy.The feasibility of the proposed method is verified with instance analysis.The experimental results show that,in comparison with the traditional GM(1,1)model,the improved model has higher fitting degree of predicted value and actual measured value,and can reduce the measurement error of the corrected throttle flow sensor effectively.