三阶多项式预测模型在红外水分仪校准方法优化中的探索和应用

Exploration and Application of Third-Order Polynomial Prediction Model in Optimization of Infrared Moisture Meter Calibration Method

为提高在线红外水分仪校准结果的准确性,保证成品烟丝含水率的稳定,本文对在线红外水分仪校准方法进行了优化,提出了基于三阶多项式预测模型的红外水分仪校准方法,并应用于实际生产控制中。该方法采用后,成品烟丝水分批次间标准偏差由0.19%下降至0.12%,表明批次间水分差异更加趋于一致。

In order to improve the accuracy of the on-line infrared moisture meter calibration results and ensure the stability of the moisture content of the finished tobacco,this paper optimizes the online infrared moisture meter calibration method,and proposes an infrared moisture meter calibration method based on the third-order polynomial prediction model,which is applied to the actual production control.After the use of this method,the standard deviation between batches of finished tobacco silk water decreased from 0.19%to 0.12%,indicating that the moisture difference between batches is more consistent.