發(fā)布時(shí)間：2018-03-26 04:06

  本文選題：COD　切入點(diǎn)：LIBS　出處：《光譜學(xué)與光譜分析》2017年11期

【摘要】：光譜學(xué)傳感技術(shù)測(cè)量水體COD是現(xiàn)代環(huán)境監(jiān)測(cè)發(fā)展的趨勢(shì),相比于傳統(tǒng)的化學(xué)分析方法具有在線連續(xù)檢測(cè)的突出優(yōu)勢(shì),適合對(duì)環(huán)境水體COD的實(shí)時(shí)監(jiān)測(cè)。采集實(shí)際水樣,利用激光誘導(dǎo)擊穿光譜技術(shù)(LIBS)獲取水樣的光譜數(shù)據(jù)。通過(guò)不同的光譜預(yù)處理方法結(jié)合偏最小二乘法建立水樣的COD定量預(yù)測(cè)模型,對(duì)水體COD的LIBS光譜測(cè)量方法的定量預(yù)測(cè)及相關(guān)模型參數(shù)進(jìn)行分析。發(fā)現(xiàn)用基線校正疊加S-G求導(dǎo)預(yù)處理后的光譜建立的PLS模型得到最佳預(yù)測(cè)效果,校正集集R2為0.9958,預(yù)測(cè)集R2為0.975 3,RMSEC為4.438 7,RMSEP為9.733 9。通過(guò)實(shí)驗(yàn)結(jié)果分析表明光譜傳感技術(shù)可用于環(huán)境實(shí)際水體COD的定量預(yù)測(cè)分析,為開(kāi)發(fā)便攜式水體檢測(cè)設(shè)備奠定了理論基礎(chǔ)。
[Abstract]:Spectroscopic sensing technology is the trend of modern environmental monitoring and development. Compared with the traditional chemical analysis method, it has outstanding advantages of on-line continuous detection, and is suitable for real-time monitoring of environmental water COD. The spectral data of water samples were obtained by laser induced breakdown spectroscopy (LIBS). The COD quantitative prediction model of water samples was established by using different spectral pretreatment methods and partial least square method. The quantitative prediction of LIBS spectrum measurement method of water body COD and the analysis of related model parameters are carried out. It is found that the best prediction effect is obtained by using the PLS model established by the pre-processing of S-G derivative preprocessing with baseline correction superposition. The corrected set R2 is 0.9958, and the prediction set R2 is 0.975 3rMSEC. The experimental results show that the spectral sensing technique can be used for quantitative prediction and analysis of COD in environmental water bodies, which lays a theoretical foundation for the development of portable water detection equipment.
【作者單位】： 桂林電子科技大學(xué);北京農(nóng)業(yè)智能裝備技術(shù)研究中心北京市農(nóng)林科學(xué)院;
【基金】：國(guó)家(863)計(jì)劃項(xiàng)目(2013AA10230202) 國(guó)家自然科學(xué)基金重點(diǎn)項(xiàng)目(31622040)資助
【分類(lèi)號(hào)】：O657.3;X832

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本文編號(hào)：1666256