近红外光谱基线漂移校正的方法研究
|
摘要
针对传统基线漂移校正方法存在校正时间较长、均方误差较高以及校正能量消耗过多等问题,提出基于小波变换的近红外光谱基线漂移校正方法。利用加权均值方法提取干涉曲线中的光谱分量,根据提取结果对光谱基线进行识别,在此基础上,引入迭代算法构建基线漂移模型。通过能量分步法确定最优小波尺度,对基线漂移模型进行最优尺度分解,将最高层的小波逼近系数重构,获取含有基线漂移信息的数据。引入趋势函数法求解出基线,利用初始数据减去基线,获取校正后的光谱数据,实现近红外光谱基线漂移校正。实验结果表明,所提方法有效降低了均方误差,提高漂移处理效果,减少校正时间以及校正能量消耗。
Aiming at the problems of traditional baseline drift correction method,such as long correction time,high mean square error and excessive correction of energy consumption,a near-infrared spectral baseline drift correction method based on wavelet transform is proposed. The weighted mean method is used to extract the spectral components in the interference curve,and the spectral baseline is identified according to the extraction result. Based on this,an iterative algorithm is introduced to construct the baseline drift model. The optimal wavelet scale is determined by the energy step method. The baseline drift model is optimally scaled,and the highest wavelet approximation coefficient is reconstructed to obtain the data with baseline drift information. The trend function method is introduced to solve the baseline,and the baseline data was subtracted from the initial data to obtain the corrected spectral data to achieve the near-infrared spectral baseline drift correction. The experimental results show that the proposed method effectively reduces the mean square error which can improve the drift processing effect,reduce the correction time and correct the energy consumption.
Aiming at the problems of traditional baseline drift correction method,such as long correction time,high mean square error and excessive correction of energy consumption,a near-infrared spectral baseline drift correction method based on wavelet transform is proposed. The weighted mean method is used to extract the spectral components in the interference curve,and the spectral baseline is identified according to the extraction result. Based on this,an iterative algorithm is introduced to construct the baseline drift model. The optimal wavelet scale is determined by the energy step method. The baseline drift model is optimally scaled,and the highest wavelet approximation coefficient is reconstructed to obtain the data with baseline drift information. The trend function method is introduced to solve the baseline,and the baseline data was subtracted from the initial data to obtain the corrected spectral data to achieve the near-infrared spectral baseline drift correction. The experimental results show that the proposed method effectively reduces the mean square error which can improve the drift processing effect,reduce the correction time and correct the energy consumption.
引文
[1]刘艳芳,卢延年,郭龙,等.基于地类分层的土壤有机质光谱反演校正样本集的构建[J].土壤学报,2016,53(2):332-341.
[2]孙晓飞,文孟喜,杨丹丹.康普顿散射线结合经验系数法校正在X射线荧光光谱测定石灰石和白云石中的应用[J].冶金分析,2016,36(1):11-17.
[3]张永刚,奚苏萍,周立,等. FTIR测量的宽波数范围发射光谱强度校正[J].红外与毫米波学报,2016,35(1):63-67.
[4]王宏博,胡秀清,张璐,等.光栅色散型成像光谱仪的偏振校正方法研究[J].光学学报,2016,36(8):126-134.
[5]李正风,徐广晋,王家俊,等.模型诊断用于近红外光谱建模校正集中奇异样本的识别[J].分析化学,2016,44(2):305-309.
[6]叶松,甘永莹,熊伟,等.采用小波变换的空间外差光谱仪基线校正[J].红外与激光工程,2016,45(11):202-206.
[7]王玲,李定明,钱红娟,等.近红外分析中的基线漂移及校正方法[J].分析试验室,2016(10):1203-1208.
[8]范贤光,王海涛,王昕,等.基于非均匀B样条的拉曼光谱基线校正算法[J].光谱学与光谱分析,2016,36(3):724-728.
[9]张文理,田逢春,赵贞贞,等.空间外差光谱仪的干涉图校正[J].光电工程,2017,44(5):488-497.
[10]南一冰,高昆,倪国强.基于波段选择估计PSF的高光谱图像运动模糊盲校正方法[J].红外与毫米波学报,2016,35(6):715-722.
[11]盛伟楠,孙翠迎,韩同帅,等.基于外部参数正交的葡萄糖近红外漫射光谱温度校正[J].纳米技术与精密工程,2017,15(5):425-429.
[12]齐海军,Karnieli,Arnon,等. Y-梯度广义最小二乘加权校正的土壤速效氮野外原位光谱预测[J].光谱学与光谱分析,2018,38(1):171-175.
[13]梁康甫,杨慧中.水质总氮在线检测的光谱数据校正方法[J].环境工程学报,2016,10(12):7396-7400.
[14]王菊香,孟凡磊,刘林密,等.样品选择结合分段直接校正法和偏最小二乘法用于近红外光谱分析模型传递研究[J].兵工学报,2016,37(1):91-96.
[15]倪力军,栾绍嵘,张立国.互联网共享模式下采用(近红外)光谱技术进行中药(材)质量快速检测的探索[J].中国中药杂志,2016,41(19):3520-3527.
[16]文韬,洪添胜,李立君,等.霉变稻谷脂肪酸含量的光谱检测模型构建与优化分析[J].农业工程学报,2016,32(1):193-199.
[2]孙晓飞,文孟喜,杨丹丹.康普顿散射线结合经验系数法校正在X射线荧光光谱测定石灰石和白云石中的应用[J].冶金分析,2016,36(1):11-17.
[3]张永刚,奚苏萍,周立,等. FTIR测量的宽波数范围发射光谱强度校正[J].红外与毫米波学报,2016,35(1):63-67.
[4]王宏博,胡秀清,张璐,等.光栅色散型成像光谱仪的偏振校正方法研究[J].光学学报,2016,36(8):126-134.
[5]李正风,徐广晋,王家俊,等.模型诊断用于近红外光谱建模校正集中奇异样本的识别[J].分析化学,2016,44(2):305-309.
[6]叶松,甘永莹,熊伟,等.采用小波变换的空间外差光谱仪基线校正[J].红外与激光工程,2016,45(11):202-206.
[7]王玲,李定明,钱红娟,等.近红外分析中的基线漂移及校正方法[J].分析试验室,2016(10):1203-1208.
[8]范贤光,王海涛,王昕,等.基于非均匀B样条的拉曼光谱基线校正算法[J].光谱学与光谱分析,2016,36(3):724-728.
[9]张文理,田逢春,赵贞贞,等.空间外差光谱仪的干涉图校正[J].光电工程,2017,44(5):488-497.
[10]南一冰,高昆,倪国强.基于波段选择估计PSF的高光谱图像运动模糊盲校正方法[J].红外与毫米波学报,2016,35(6):715-722.
[11]盛伟楠,孙翠迎,韩同帅,等.基于外部参数正交的葡萄糖近红外漫射光谱温度校正[J].纳米技术与精密工程,2017,15(5):425-429.
[12]齐海军,Karnieli,Arnon,等. Y-梯度广义最小二乘加权校正的土壤速效氮野外原位光谱预测[J].光谱学与光谱分析,2018,38(1):171-175.
[13]梁康甫,杨慧中.水质总氮在线检测的光谱数据校正方法[J].环境工程学报,2016,10(12):7396-7400.
[14]王菊香,孟凡磊,刘林密,等.样品选择结合分段直接校正法和偏最小二乘法用于近红外光谱分析模型传递研究[J].兵工学报,2016,37(1):91-96.
[15]倪力军,栾绍嵘,张立国.互联网共享模式下采用(近红外)光谱技术进行中药(材)质量快速检测的探索[J].中国中药杂志,2016,41(19):3520-3527.
[16]文韬,洪添胜,李立君,等.霉变稻谷脂肪酸含量的光谱检测模型构建与优化分析[J].农业工程学报,2016,32(1):193-199.