摘要
根据测量仪器的实际状态进行校准间隔的预测,可有效地避免不足校准和过剩校准。该文分析了历史校准数据的特征,对于既含有线性因素又含有指数因素的历史校准数据序列,建立动态灰色线性回归预测模型,预测测量仪器的校准间隔。动态灰色线性回归模型有机地将灰色GM(1,1)模型和线性模型组合起来,通过新老数据的新陈代谢,更加真实地反映系统的特征。通过实验对预测模型进行验证,结果表明:动态灰色线性回归模型的拟合与预测精度高于单纯的灰色GM(1,1)模型及新陈代谢GM(1,1)模型。
Prediction of the calibration interval for the measuring instrument could effectively prevent the lack calibration and excessive calibration.This article analyzed features of historical calibration data.And a dynamical grey linear regression model was established for the historical calibration data including linear factors and exponential factors.This model effectively combined the linear model with the GM（1,1） model,exactly reflected the features of the system.The validity of the model also was tested by through experiments.The results demonstrated that the precision of the dynamical grey linear regression model was higher than the GM（1,1） model or the innovation GM（1,1） model.Therefore,the model is a suitable model to predict the calibration interval of measurement instruments.
出处
《中国测试》
CAS
北大核心
2013年第1期39-42,共4页
China Measurement & Test
关键词
测量仪器
校准
校准间隔
预测
灰色线性回归模型
measuring instrument
calibration
calibration interval
prediction
grey linear regression model
