衰减全反射-傅里叶红外光谱高阶导数结合角度量的最小二乘预测风电机组润滑油酸值  

Prediction of Wind Turbine Lubricating Oil′s Acid Value by Ordinary Least Square Method Based on Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy Through Higher-Order Derivative Combined with Angular Metric

作　　者：葛春晖 刘妍君 陈梦实 杨策 梁培沛 姚志湘[3] 张锴[1] GE Chun-Hui;LIU Yan-Jun;CHEN Meng-Shi;YANG Ce;LIANG Pei-Pei;YAO Zhi-Xiang;ZHANG Kai(Beijing Key Laboratory of Emission Surveillance and Control for Thermal Power Generation,North China University of Electric Power,Beijing 102206,China;Longyuan(Beijing)New Energy Engineering Technology Co.Ltd.,Beijing 100034,China;College of Biological and Chemical Engineering,Guangxi University of Science and Technology,Liuzhou 545006,China)

机构地区：[1]华北电力大学,热电生产过程污染物监测与控制北京市重点实验室,北京102206 [2]龙源(北京)新能源工程技术有限公司,北京100034 [3]广西科技大学生物与化学工程学院,柳州545006

出　　处：《分析化学》2024年第9期1254-1265,共12页Chinese Journal of Analytical Chemistry

基　　金：国家自然科学基金联合基金重点项目(No.U1910215)资助。

摘　　要：针对多元统计建模依赖大样本的关键限制性问题,提出了高阶导数处理结合向量空间角度量乘性误差校正的最小二乘回归方法,并建立了衰减全反射-傅里叶红外光谱(ATR-FTIR)酸值预测模型。以某风电机组96个润滑油样品为案例,基于电位滴定法酸值测定数据实现了ATR-FTIR光谱对酸值的直接校正预测。采用模拟双曲函数法(SH)得到精密且准确的四阶导数光谱,通过分离重叠区域,提高光谱选择性;从校正集(48个样本)中按照相关系数判断特征区域;选取酸值最高样本作为参比,以角度量转换、1/(1+tan(θ/2))作为光谱的度量关系,抑制ATR-FTIR中有效光程变化等因素引起的乘性误差。经过四阶导数结合角度量方法的有效预处理,变量数由1737降至8,条件数由1.85×1015降至56.34,有效消除了共线性对最小二乘(OLS)法的影响。直接应用OLS回归,验证集47个样本的决定系数(R^(2))达到0.981,相对误差为–8.38%~8.22%,优于常用的偏最小二乘(PLS)方法(R^(2)=0.865,相对误差为–27.82%~22.38%),有效的数据预处理显著提高了预测精度。为进一步验证样本数对模型的影响,将校正样本集压缩至25,验证集扩充至70。结果表明,此模型的变量数由1737降为8,条件数由3.88×10^(15)降至42.60,验证集的R^(2)=0.972,相对误差为–10.80%~12.31%,较PLS方法(R^(2)=0.724,相对误差为–34.26%~53.84%)改善更明显,表明本方法在更少的建模样本条件下依然具有较高的预测精度,同时对乘性误差干扰具有良好的抑制作用和鲁棒性。To address the key challenges in multivariate statistical modeling,a higher-order derivative approach combined with vector space angle multiplicative error correction was proposed for establishing an acid value prediction ordinary least squares(OLS)regression model based on attenuated total reflectance-Fourier transform infrared(ATR-FTIR)spectroscopy.By using acid values measured by potentiometric titration as reference,ATRFTIR spectroscopy was utilized for direct calibration and prediction of acid values on 96 kinds of lubricating oil samples from a wind turbine.Firstly,the simulated hyperbolic(SH)method was employed to obtain accurate fourth derivative spectrum,resolving overlapping bands and enhancing spectral selectivity.Then,from the calibration set(48 samples),informative spectral regions were identified based on correlation coefficients.Next,the sample with the highest acid value was selected as the reference and 1/1+tan/2(())was used as the metric relation of the spectrum to suppress the multiplicity error caused by factors such as the change of effective optical path in ATRFTIR spectroscopy.After pretreatment of the spectrum by the method of fourth-order derivative combined with angular quantity,the number of variables decreased from 1737 to 8,and the matrix condition number decreased from 1.85×10^(15) to 56.34,which effectively eliminated the collinearity issue for OLS regression.Direct OLS modeling on spectral preprocessed data achieved a determination coefficient of 0.981 for 47 validation samples,with a relative error range of–8.38%–8.22%,outperforming the commonly used partial least squares(PLS)method(Determination coefficient of 0.865,relative error of–27.82%–22.38%).It was proved that effective data preprocessing significantly improved the prediction accuracy of the model.Furthermore,when the number of calibration set was compressed to 25 and the number of validation set was expanded to 70,the model retained 8 variables with a condition number of 42.60,the determination coefficient of val

关 键 词：润滑油 酸值 衰减全反射-傅立叶红外光谱 高阶导数 向量空间角 共线性 最小二乘回归 

分 类 号：TM315[电气工程—电机] O657.33[理学—分析化学] TE626.3[理学—化学]