Research On Measurement Technique And Application Of Laser-induced Fluorescence Lifetime Imaging

Laser induced fluorescence detection technology is the basis of active fluorescence radar remote sensing monitoring.Traditional fluorescence detection technique is difficult to realize remote sensing detection due to the influence of external factors such as excitation light intensity,ambient light intensity,fluorescence scattering angle and so on.Fluorescence lifetime,which the decay time of fluorescence signal,has the advantage of strong stability when it can be used detection because it is not affected by the external ambient light.Due to its visualization and mapping of the two-dimensional spatial characteristic distribution of the measured fluorescent substances,the fluorescence lifetime map has attracted wide attention in recent years.Therefore,the study of fluorescence lifetime imaging detection technology has important scientific research significance and application value to solve the problems in traditional fluorescence remote sensing detection,such as vulenerable to environmental interference,and to realized large-scale and high-sensitivity detection.Aiming at the problem that fluorescence intensity signal is easy to be interfered,a fluorescence lifetime imaging measurement system is designed using fluorescence lifetime parameter as the measurement object.According to the principle that different substances because of different different molecular structure have different fluorescence spectra and fluorescence life under laser excitation,the specificity of fluorescence spectra and fluorescence life is used to detected and distinguish different pollutants.It was carried out that the imaging detection of fluorescence lifetime with oil pollutions and plant chlorophyll as research targets.In view of the phenomenon that oil fluorescence is excited by pulsed laser,the attenuation process fluorescence signal was recorded by a high-speed detection imaging system.Using the multi-exponential decay function,the fluorescence decay process was fitting according to the nonlinear least square method,and the parameters of fluorescence lifetime were calculated to realize the detection and identification of oils.Oil type identification and traceability is a technical difficulty in oil pollution monitoring.Based on the analysis of the shortcoming of current machine learning methods based on spectral analysis,the support vector machine learning method was proposed according the average lifetime of fluorescence and the occurrence time of secondary peaks as the characteristic parameters.The selection and parameters of different kernel functions were optimized,and the identification model of oil pollution was constructed.The experiment results show that the average recognition rate could reach above 90%.The distortion phenomenon of fluorescence lifetime image was studied in measuring the chlorophyll fluorescence life of plant leaves with the fluorescence lifetime image measurement system.Analyzing the cause of distortion,the correction method of image distortion was proposed.In the process of measurement,the change of surrounding environment caused the laser speckle jitter thus the laser-induced fluorescence have changed,and the fluorescence lifetime image have distorted.Based on the principle of speckle cross-correlation,by analyzing the rules of laser speckle jitter and fluorescence paticle displacement caused by external environmental factors,the correction of distorted images is realized by inverting the fluorescence lifetime of distortion points displacement using the displacement compensation method.Experimental results show that the effective rate of compensating the fluorescence life of distortion points by diaplacement compensation principle is more than 18%,and the relative error of inversing fluorescence lifetime of distortion points is less than 30%.Aiming at the application requirements of two-dimensional and three-dimensional remote sensing detection and monitoring in the field of environmental monitoring and agricultural production,the remote sensing system of laser induced fluorescence lidar was proposed and constructed,and the system simulation research was carried out in this thesis.Based on the lidar equation,the effects of various parameters of the transmitting system and the receiving system on the system performance were analyzed according to study the fluorescence characteristics of oil pollutants.Through simulation analysis,it was verified that feasibility of monitoring surface oil pollutants with lidar remote sensing technology,and it was optimized that the parameters of remote sensing system.The laser-induced fluorescence lidar system is not only suitable for monitoring surface oil pollution in the environment field,but also for remote sensing monitoring of other fluorescence substances.The works will provide basic theoretical support for the research and development of lidar system design in remote sensing monitoring field.Theoretical researches and experimental analysis results show that laser-induced fluorescence lifetime imaging detection technique can not only measure the fluorescence lifetime effectively,but also display the two-dimensional spatial distribution of the fluorescence lifetime.The fluorescence lifetime can not only be used as the basis for the identification of pollutants,but also can show th changes of material microenvironment.The work in this thesis will promote the development of environmental remote sensing detection technology for our country.A new detection tool for environment monitoring research will be provided.