Novel Detection of Atmospheric Turbulence Profile Using Mie-Scattering Lidar Based on Non-Kolmogorov Turbulence Theory.

Turbulence can cause effects such as light intensity fluctuations and phase fluctuations when a laser is transmitted in the atmosphere, which has serious impacts on a number of optical engineering application effects and on climate improvement. Therefore, accurately obtaining real-time turbulence intensity information using lidar-active remote sensing technology is of great significance. In this paper, based on residual turbulent scintillation theory, a Mie-scattering lidar method was developed to detect atmospheric turbulence intensity. By extracting light intensity fluctuation information from a Mie-scattering lidar return signal, the atmospheric refractive index structure constant, Cn2, representing the atmospheric turbulence intensity, could be obtained. Specifically, the scintillation effect on the detection path was analyzed, and the probability density distribution of the light intensity of the Mie-scattering lidar return signal was studied. It was verified that the probability density of logarithmic light intensity basically follows a normal distribution under weak fluctuation conditions. The Cn2 profile based on Kolmogorov turbulence theory was retrieved using a layered, iterative method through the scintillation index. The method for detecting Kolmogorov turbulence intensity was applied to the detection of the non-Kolmogorov turbulence intensity. Through detection using the scintillation index, the corresponding C˜n2 profile could be calculated. The detection of the C˜n2 and Cn2 profiles were compared with the Hufnagel-Valley (HV) night model in the Yinchuan area. The results show that the detection results are consistent with the overall change trend of the model. In general, it is feasible to detect a non-Kolmogorov turbulence profile using Mie-scattering lidar.

Monitoring and predicting Fusarium wilt disease in cucumbers based on quantitative analysis of kinetic imaging of chlorophyll fluorescence.

Cucumber (Cucumis sativus L.) is a widely cultivated and economically profitable crop. However, Fusarium wilt disease can seriously affect cucumber yields, as it is difficult to prevent and eliminate. Therefore, a reliable method is needed for the rapid and early detection of Fusarium infection in cucumbers, which could be provided via the kinetic imaging of chlorophyll fluorescence (ChlF). In this study, ChlF imaging and kinetic parameters were utilized with gray and radial basis function models to monitor cucumber Fusarium wilt disease. The results indicate that the disease can be detected and predicted using this imaging technique before symptoms become visible.

Preliminary measurements of fluorescent aerosol number concentrations using a laser-induced fluorescence lidar.

A laser-induced fluorescence lidar has been developed for detecting the concentration of fluorescent aerosols in the air. The fluorescence lidar was constructed with a pulsed fourth-harmonic Nd:YAG laser at the ultraviolet wavelength of 266 nm with a repetition rate of 10 Hz. A 250 mm diameter custom telescope was used to collect optical spectra ranging from 260 to 560 nm. Fluorescence signals with wavelengths ranging from 310-440 nm were extracted, exploring a filter with a bandwidth of 130 nm. The preliminary experiments were conducted at the campus of Xi'an University of Technology, in which the fluorescence signals of atmospheric fluorescent aerosols were continuously collected from 20:00 to 23:00 CST on 13 December 2017. Based on the fluorescence lidar equation, the density of fluorescence signals was calibrated using Rayleigh-Mie scattering signals and ozone (O3) concentration data at the ground level. Measured ranges show a strong dependence with the O3 concentrations due to its absorption characteristics at ultraviolet 266 nm. Moreover, the concentration of the biogenic particles was also calculated based on the raw data of the fluorescence channel. Obtained results show that the concentration of biogenic particles in the Xi'an area varied greatly, ranging from 3456 particles · m-3 to 8835 particles · m-3 during winter.

Investigation of contact pressure and influence function model for soft wheel polishing.

The tool influence function (TIF) is critical for calculating the dwell-time map to improve form accuracy. We present the TIF for the process of computer-controlled polishing with a soft polishing wheel. In this paper, the static TIF was developed based on the Preston equation. The pressure distribution was verified by the real removal spot section profiles. According to the experiment measurements, the pressure distribution simulated by Hertz contact theory was much larger than the real contact pressure. The simulated pressure distribution, which was modeled by the Winkler elastic foundation for a soft polishing wheel, matched the real contact pressure. A series of experiments was conducted to obtain the removal spot statistical properties for validating the relationship between material removal and processing time and contact pressure and relative velocity, along with calculating the fitted parameters to establish the TIF. The developed TIF predicted the removal character for the studied soft wheel polishing.