阐述了 GM(1,1)模型的建模过程;探讨了灰色预测理论在传感器自校正技术应用中的局限性,并针对其局限性提出解决方案,即通过 GM(1,1)模型预测出传感器最终的测量输出值输出和误差变化量,再结合单片机技术,对传感器输出进行动态补偿,从而达到自校正的目的。其实验结果表明,应用该方法得到的预测值与真值的拟合程度好,预测值与真值之间最大差值为0.1499%,而该处校正前的差值为0.3000%,提高了传感器的测量精度。 The modeling process of the GM (1,1) model is expounded. The limitations of the gray prediction theory in the application of the sensor self-tuning technique are discussed. A solution to the limitations of the method is proposed, that is, the GM (1,1) model is used to predict The final output of the sensor to measure the output value and error changes, combined with microcontroller technology, the dynamic output of the sensor to compensate, so as to achieve the purpose of self-calibration. The experimental results show that the predicted value obtained by this method fits well with the true value, the maximum difference between the predicted value and the true value is 0.1499%, while the difference before correction is 0.3000%, which improves the accuracy of the sensor The measurement accuracy.