Research On Detection Of Petroleum Pollutants Based On Fluorescence Spectroscopy Technology

With the continuous development of oil resources in the ocean,the oil leaking into the marine environment is also increasing.It not only threatens the marine ecological environment,but also seriously affects people’s health.Therefore,the rapid and effective detection of petroleum pollutants in the marine environment is of great significance for protecting the marine ecological environment and human health.Petroleum products contain a large amount of polycyclic aromatic hydrocarbons,which have strong fluorescence characteristics.Compared with traditional fluorescence spectroscopy analysis technology,three-dimensional fluorescence spectroscopy analysis technology has gradually become one of the important methods of petroleum pollutant detection due to its fast analysis speed,high sensitivity,and low damage intensity.This paper will adopt an analysis strategy based on three-dimensional fluorescence spectroscopy technology and combining feature data extraction algorithms,multi-dimensional correction algorithms in chemometrics,and pattern recognition methods to finally achieve efficient and accurate qualitative and quantitative analysis of petroleum pollutants.Based on the principle of photoluminescence,this article elaborates the specific detection process of fluorescence spectroscopy technology and the basic characteristics of three-dimensional fluorescence spectroscopy;briefly describes several commonly used fluorescence spectroscopy analysis methods,and introduces the spectral characteristics of three-dimensional fluorescence spectroscopy in detail,and confirms feasibility of oil pollutant detection of fluorescence spectroscopy.In order to achieve the classification and identification of complex multi-component petroleum pollutants,the representative diesel,aviation kerosene,gasoline and lubricants in petroleum mixtures are used as the research objects,establish an analysis strategy based on three-dimensional fluorescence spectroscopy technology,combined with NMF algorithms and pattern recognition methods to achieve accurate classification of oil pollutants.Through the design of specific experiments,after preprocessing the collected three-dimensional fluorescence spectrum data,the two-dimensional characteristic spectrum data is extracted by ysing the feature extraction algorithm to realize the component characterization,and then three classification models are constructed,and the classification effect is compared according to the classification accuracy,sensiticity and specificity.This analysis strategy effectively realizes the classification and identification of petroleum pollutant mixed solutions,and provides a new idea for the detection of petroleum pollutants in the marine environment.In order to further improve the classification accuracy,on the basis of the third chapter,the PARAFAC algorithm of the second-order correction algorithm is introduced,and another analysis strategy is also obtained by combining with the pattern recognition method.The PARAFAC algorithm is used to analyze the three-dimensional fluorescence spectrum data,and the meaningful components are characterized and analyzed.Three classification models are also constructed,and the classification effect is compared and analyzed according to the evaluation criteria.Compared with the analysis method in the third chapter,the classification accuracy of this analysis strategy has been significantly improved,which effectively solves the problem of classification and identification of mixed petroleum pollutants in complex system.The pH value of ocean is introduced as a new dimension in the experiment,and a fourdimensional response matrix of excitation wavelength-emission wavelength-p H-number of samples is constructed.On the basis of three-dimensional fluorescence spectroscopy technology,combined with a third-order calibration algorithm,qualitative analysis and quantitative concentration prediction of petroleum pollutants are carried out.The study compares the performance of APQLD algorithm and AWRCQLD algorithm in qualitative analysis,and calculates and evaluates the average recovery rate,predicted root mean square error and relative error of the two algorithms,and evaluates the quality factor parameters of quantitative analysis skills.This analysis strategy shows that even if new interference factors are introduced,the third-order calibration algorithm can still perform accurate qualitative analysis and quantitative concentration prediction of petroleum pollutants.