计算机与应用化学
計算機與應用化學
계산궤여응용화학
COMPUTERS AND APPLIED CHEMISTRY
2013年
3期
246-250
,共5页
郑开逸%范伟%吴婷%胡慧廉%杜一平%梁逸曾
鄭開逸%範偉%吳婷%鬍慧廉%杜一平%樑逸曾
정개일%범위%오정%호혜렴%두일평%량일증
三组分体系%模型转移%CCA%PDS%测定时间%近红外光谱仪
三組分體繫%模型轉移%CCA%PDS%測定時間%近紅外光譜儀
삼조분체계%모형전이%CCA%PDS%측정시간%근홍외광보의
tri-component mixtures%calibration transfer%CCA%PDS%measurement dates%NIR instruments
以甲苯、氯苯和正庚烷混和三组分体系为分析样品,应用模型转移法来校正不同仪器和不同测量时间导致的近红外光谱之间的差异。在校正测量时间导致的差异时,以16日由 Bruker 近红外光谱仪扫描的光谱作为主光谱,而17日由同台仪器扫描的光谱作为从光谱。在校正仪器导致的光谱差异时,以16日由 Bruker 近红外光谱仪扫描的光谱作为主光谱,而在同一天由 Perkin-Elmer 近红外光谱仪扫描的光谱作为从光谱。采集光谱后,用分段直接校正(PDS)和典型相关分析(CCA)校正从光谱。结果显示:虽然仪器和测量时间差别均导致从光谱偏离主光谱,但是 CCA 的效果更佳,使得校正后的从光谱能用主光谱的模型准确预测样品含量。
以甲苯、氯苯和正庚烷混和三組分體繫為分析樣品,應用模型轉移法來校正不同儀器和不同測量時間導緻的近紅外光譜之間的差異。在校正測量時間導緻的差異時,以16日由 Bruker 近紅外光譜儀掃描的光譜作為主光譜,而17日由同檯儀器掃描的光譜作為從光譜。在校正儀器導緻的光譜差異時,以16日由 Bruker 近紅外光譜儀掃描的光譜作為主光譜,而在同一天由 Perkin-Elmer 近紅外光譜儀掃描的光譜作為從光譜。採集光譜後,用分段直接校正(PDS)和典型相關分析(CCA)校正從光譜。結果顯示:雖然儀器和測量時間差彆均導緻從光譜偏離主光譜,但是 CCA 的效果更佳,使得校正後的從光譜能用主光譜的模型準確預測樣品含量。
이갑분、록분화정경완혼화삼조분체계위분석양품,응용모형전이법래교정불동의기화불동측량시간도치적근홍외광보지간적차이。재교정측량시간도치적차이시,이16일유 Bruker 근홍외광보의소묘적광보작위주광보,이17일유동태의기소묘적광보작위종광보。재교정의기도치적광보차이시,이16일유 Bruker 근홍외광보의소묘적광보작위주광보,이재동일천유 Perkin-Elmer 근홍외광보의소묘적광보작위종광보。채집광보후,용분단직접교정(PDS)화전형상관분석(CCA)교정종광보。결과현시:수연의기화측량시간차별균도치종광보편리주광보,단시 CCA 적효과경가,사득교정후적종광보능용주광보적모형준학예측양품함량。
Calibration transfer methods were used to correct near infrared spectra (NIR) of tri-component mixtures including methylbenzene, chlorobenzene and n-heptane for their variations resulting from differences of measurement date and instrument. For correcting spectra between different measurement dates and instruments the spectra of mixtures measured in spectrometer of Bruker on date 16 were assigned as primary spectra while the spectra of same mixtures detected in spectrometer of Bruker on date 17 and in spectrometer of Perkin-Elmer on date 16 were set as secondary spectra for changes of measurement date and instrument respectively. After spectra obtained, two calibration transfer methods including canonical correlation analysis (CCA) and piecewise direct standardization (PDS) were used to correct the secondary spectra. The results showed that although variations of both measurement date and instrument can cause secondary spectra to deviate from primary spectra, the CCA can correct the secondary spectra to use the model of primary spectra to predict those three components with high accuracy.