Siying Chen

Characterization of edible oils using time-resolved fluorescence

To analyze and detect edible oils, a spectral recognition method is introduced based on time-resolved fluorescence (TRF). Contour diagrams of TRF intensities superior to steady-state fluorescence are constructed to serve as unique fingerprints for edible oils, which can be used to identify vegetable oils. The proposed approach provides a rapid and reliable means for analyzing and classifying edible oils in food security research fields. Reliability and stability are verified by TRF measurements of peanut oils of three brands in a supplementation trial.

Classification of edible oils using 532 nm laser-induced fluorescence combined with support vector machine

In this paper, laser-induced fluorescence (LIF) is used to characterize and distinguish between different vegetable oils, including soybean, olive, grapeseed, rapeseed, corn, peanut, sunflower, canola, and walnut oils. A 532 nm laser, rather than an ultraviolet (UV) light source, is proposed and used as an excitation light source for the fluorescence analysis of edible oils. It was found that this laser is superior to UV lasers, the fluorescent characteristics become more distinct under 532 nm laser excitation. Edible oils were differentiated by LIF combined with principal component analysis which was used to reduce the dimensionality of data by finding key attributes, and support vector machine. This paper demonstrates, that for ten popular edible oils, the recognition rate can reach up to 100% when a 532 nm laser serves as an excitation light source.

Motor Oil Classification Based on Time-Resolved Fluorescence

A time-resolved fluorescence (TRF) technique is presented for classifying motor oils. The system is constructed with a third harmonic Nd:YAG laser, a spectrometer, and an intensified charge coupled device (ICCD) camera. Steady-state and time-resolved fluorescence (TRF) measurements are reported for several motor oils. It is found that steady-state fluorescence is insufficient to distinguish the motor oil samples. Then contour diagrams of TRF intensities (CDTRFIs) are acquired to serve as unique fingerprints to identify motor oils by using the distinct TRF of motor oils. CDTRFIs are preferable to steady-state fluorescence spectra for classifying different motor oils, making CDTRFIs a particularly choice for the development of fluorescence-based methods for the discrimination and characterization of motor oils. The two-dimensional fluorescence contour diagrams contain more information, not only the changing shapes of the LIF spectra but also the relative intensity. The results indicate that motor oils can be differentiated based on the new proposed method, which provides reliable methods for analyzing and classifying motor oils.

Determining the orientation of transition moments and depolarization by fluorescence polarizing angle spectrum

In this paper, fluorescence polarizing angle spectrum, combined with degree of polarization(DOP), is proposed to determine the spatial orientation of transition dipole moments (TDMs) and depolarization of chlorophyll in solution. It is found that, due to the oriented TDMs under polarized laser excitation, the projections of angle of polarization(AOP) and DOP on the three orthogonal planes are different from each other. Experiments demonstrate that we can acquire the spatial orientation by detecting the projections of AOP on two orthogonal planes (xOz and yOz). Meanwhile, The depolarization can also be determined by the DOP spectrums. The validity of this method has been verified by another projection on the xOy plane.

Robust calibration method for pure rotational Raman lidar temperature measurement.

A new calibration method for pure rotational Raman lidar temperature measurement is described in this work. The method forms a temperature-dependent term in the intensity ratio, which is calculable with the radiosonde data, and then derives a calibration factor, with which the temperature is retrievable from the lidar return. The method is demonstrated and compared with existing methods through simulations and experiments. Results of the comparison show that the proposed method could provide more accurate calibrations under low signal-to-noise ratio conditions and could thus reduce the lidar performance requirement for temperature retrieval.

Fluorescence polarization technique: a new method for vegetable oils classification

Concern about classification of different edible oils has risen recently in food safety. Developing an effective oil classification method is essential for public health. In this paper, a novel fluorescence polarization technique is developed to classify various types of oils. The degree of polarization (DOP) spectra of seven vegetable oils are collected and analyzed. Classification of olive oil, walnut oil, and other types of oils is successfully achieved with DOP spectra under 532 nm laser excitation. A classification accuracy of 100% is obtained for the investigated samples. The method is non-destructive and requires no sample preparation, which provides insight to develop a novel portable monitor system concerning food safety.

Analyzing fluorophore electronic structure and depolarization by fluorescence polarizing angle spectrum

In this Letter, a method, based on stokes parameters, is developed to observe the angular displacement between the excitation and emission moments. Experiments demonstrate that when combined with degree of polarization spectrums, we can acquire the depolarization caused by angular displacement or energy migration. The method presented in this Letter can be easily realized with the existing fluorescence measuring system and may potentially make it convenient to study the fluorophore electronic structure or the mechanism of fluorescence anisotropy.

Noise modeling by the trend of each range gate for coherent Doppler LIDAR

Abstract. A denoising method of all-fiber pulsed coherent Doppler LIDAR (CDL) is investigated. The goal is to enhance the signal-to-noise ratio (SNR) in the weak signal regime. Based on differential detection theory, the total noise expression of CDL with a dual-balanced detector is introduced and analyzed. The conclusion is drawn that the total noise can be acquired under the local oscillator laser exposure conditions by reasonable simplification. Using the actual measured data, the ratio of the standard deviation to the mean value of the total noise in each range gate is obtained and is up to approximately 11%. In order to suppress the jitter of the noise, an effective noise modeling by the trend of each range gate is developed. The feasibility of this method is verified by a long set of measured data. The spatial and temporal distribution of wind speed is illustrated with 400 pulses accumulation. Compared to the noise modeling of the tail, the detection range of wind speed using the proposed method can be improved by 35.3%.

Automatic road extraction for airborne lidar data

Airborne LiDAR, as a precise and fast earth’s surface three-dimensional (3D) measuring method, has been widely used in the past decades. It provides a new approach for acquiring road information. By analyzing the characteristics of LiDAR datasets as well as that of the road in the datasets, a morphological method has been proposed to automatically extract the road from airborne LiDAR datasets. Firstly, ground points are segmented from raw LiDAR data by morphological operations. The key factor in this process is how to select the window sizes in different scale spaces, and setting the elevation threshold to prevent over-segmentation in each scale space. Secondly, candidate road points are segmented from the ground points, which are obtained from previous step, by intensity constraint, local point density and region area constraint, and so on. Thirdly, morphological opening operation and closing operation were used to process the candidate road points segmented from above steps. The opening operation may effectively filter the noise areas, and greatly maintain the road detail. The closing operation may fill the small holes within the road, connecting nearby roads, and smoothing the road boundary, without signification area change. The main road can be extracted from the raw airborne LiDAR points by previous three steps. Finally, the proposed method has been verified by LiDAR data which consists of complex road networks. The result shows that the proposed method can automatically extract road from airborne LiDAR data with higher efficiency and precision.

A new method for obtaining aerosol backscattering ratio with partial pure rotational Raman spectrum

The error of retrieving the aerosol backscattering ratio with partial Raman spectrum is calculated in present paper. A new method is presented for reducing the error. One low-level and one high-level spectrum line are chose to make up a new pseudo-line independent on the temperature. Finally, aerosol backscattering coefficient ratio profiles of the atmosphere were obtained from the signals of a rotational Raman Lidar in our lab. The results show that Tropospheric aerosol backscattering coefficient ratio can be retrieved by using the new rotational Raman pseudo-line without considering the relation between aerosol extinction and backscattering.