本文選題：熒光特性　切入點(diǎn)：離散小波變換　出處：《光譜學(xué)與光譜分析》2017年11期 　論文類(lèi)型：期刊論文

【摘要】：采用恒波長(zhǎng)同步熒光光譜法檢測(cè)分析8種燃料油、7種中東原油、14種非中東原油的熒光特征,結(jié)合離散小波變換以及Fisher判別法建立海上溢油油種鑒別的模型。29種油樣風(fēng)化前后均在波長(zhǎng)(280±2),(302±2),(332±2)和(380±2)nm處有典型的熒光峰,但在(380±2)nm處風(fēng)化油樣的熒光強(qiáng)度的離散度過(guò)大,該波長(zhǎng)不適于油種鑒別。在db7小波基函數(shù)下對(duì)29種原始油樣熒光譜圖進(jìn)行6層分解,提取d3細(xì)節(jié)系數(shù)特征,確定波長(zhǎng)(255±2),(280±2),(302±2),(332±2)和(354±2)nm處的小波系數(shù)并用于Fisher判別模型建立。29種油樣在(280±2)nm處均有極值點(diǎn),燃料油小波系數(shù)位于44.06±5.62之間,原油位于22.47±5.12之間,此波長(zhǎng)處的小波系數(shù)可區(qū)分燃料油與原油。建立的Fisher判別模型不僅能區(qū)分燃料油和原油還能進(jìn)一步區(qū)分中東原油,Wilks's lambda分布所對(duì)應(yīng)的P值分別為0和0.02,表明模型是可行的。模型驗(yàn)證結(jié)果顯示,對(duì)風(fēng)化后的建模油樣的鑒別正確率達(dá)到96.6%,對(duì)非建模23種油樣鑒別正確率達(dá)到95.7%。由于建模油樣風(fēng)化前后的修正余弦相似度為0.91~0.98,因而以未風(fēng)化油樣建立的油種鑒別模型同樣適用于風(fēng)化后油樣的辨別。
[Abstract]:The fluorescence characteristics of 14 kinds of non-Middle Eastern crude oil from 8 kinds of fuel oil and 7 kinds of Middle East crude oil were detected and analyzed by constant wavelength synchronous fluorescence spectrometry. Combined with discrete wavelet transform (DWT) and Fisher discriminant method, the model of oil spill identification at sea. 29 oil samples have typical fluorescence peaks at wavelength of 280 鹵2, 302 鹵2, 332 鹵2) and 380 鹵2 nm before and after weathering, but the dispersion of fluorescence intensity of weathered oil samples at 380 鹵2 nm is very large. The wavelength is not suitable for oil identification. The fluorescence spectra of 29 original oil samples are decomposed into six layers under db7 wavelet basis function, and the characteristics of d3 detail coefficients are extracted. The wavelet coefficients at the wavelength of 255 鹵2, 280 鹵2 ~ 2, 302 鹵2 ~ 2 and 354 鹵2 ~ 2 nm were determined and used to establish a Fisher discriminant model. All 29 oil samples had extreme values at 280 鹵2 ~ 2 nm. The wavelet coefficients of fuel oil were between 44.06 鹵5.62 and 22.47 鹵5.12, and the wavelet coefficients of fuel oil were in the range of 44.06 鹵5.62 and 22.47 鹵5.12, respectively, and the results showed that the wavelet coefficients of fuel oil were in the range of 44.06 鹵5.62 and 22.47 鹵5.12, respectively. The wavelet coefficients at this wavelength can distinguish fuel oil from crude oil. The established Fisher discriminant model can not only distinguish fuel oil from crude oil, but also further distinguish Middle East crude oil Wilksworth's lambda distribution corresponding to P values of 0 and 0.02, respectively. Feasible. Model validation results show that, After weathering, the accuracy rate of oil sample identification was 96.6, and that of 23 unmodeled oil samples was 95.70.The modified cosine similarity before and after weathering of the model oil sample was 0.910.98, so the oil identification model was established by using unweathered oil sample. Type A also applies to the identification of oil samples after weathering.
【作者單位】： 大連海事大學(xué)環(huán)境科學(xué)與工程學(xué)院;
【基金】：中央高校基本科研業(yè)務(wù)費(fèi)專(zhuān)項(xiàng)資金項(xiàng)目(01760516)資助
【分類(lèi)號(hào)】：X55;X834

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