基于残差补偿灰色马尔科夫模型的校准间隔预测方法

纪伊琳; 钱政

纪伊琳,钱政.基于残差补偿灰色马尔科夫模型的校准间隔预测方法[J].电测与仪表,2017,54(21):.
JI Yilin,QIAN Zheng.Prediction of Calibration Interval Based on Residual Compensation Grey-Markov Model[J].Electrical Measurement & Instrumentation,2017,54(21):.

基于残差补偿灰色马尔科夫模型的校准间隔预测方法

Prediction of Calibration Interval Based on Residual Compensation Grey-Markov Model

DOI：

中文关键词: 校准间隔残差补偿灰色GM(1,1)模型马尔科夫模型

英文关键词:calibration interval, residual compensation, GM(1,1) model, Markov model

基金项目:基于多源数据融合的风电机组健康状态评估及预测方法国家自然科学基金资助项目（61573046）

作者中文名	作者英文名	单位
纪伊琳	JI Yilin	北京航空航天大学
钱政	QIAN Zheng	北京航空航天大学

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中文摘要:

为了实现对测量仪器科学、合理的校准间隔的预测,根据历史数据的特点,将灰色预测模型与马尔科夫预测方法相结合,用灰色GM(1,1)模型预测校准数据的总体变化趋势,用马尔科夫模型预测残差序列的状态变化,进而得到校准数据的预测值。用实验数据对模型进行了验证。结果表明,模型很好地体现了测量仪器关键参数的发展过程,适于校准间隔的预测。

英文摘要:

To predict the calibration interval of a measuring instrument scientifically, characters of historical calibration data are analyzed, and a combination of GM(1,1) model and Markov method is adopted to acquire the predictive value of calibration data. GM(1,1) model is used to forecast the general trend of the calibration data, and Markov model is used to predict the state of residual series. Experiments are utilized to validate the model. The results demonstrate that the model can well forecast the evolvement of key parameters of a measuring instrument, which means the model is suitable for calibration interval prediction.

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