The particle size of submicron particles significantly affects their properties; thus, the accurate measurement of submicron particle size is essential to ensure its excellent properties. Polarized light scattering is an important tool for measuring the particle size of the ensemble of particles in suspension. However, in the existing measurement systems, the polarized scattered light is detected using a CCD detector or an array of single-point detectors. The CCD detector misses a large part of the polarized scattered light due to its narrow detection range of scattering angles, and the array of single-point detectors has the problem of low angular resolution due to the limited number of detectors. According to the above problems, this paper designs a submicron particle size measurement method based on the polarization difference in polarized scattered light with high angular resolution. The vertically and horizontally polarized scattered light was acquired with high angular resolution (angular separation = 2°) over a scattering angle range of 50°–110° using a photomultiplier coupled with a turntable. The scattering angle of the acquired vertically and horizontally polarized scattered light were corrected to eliminate the scattering angle deviations caused by obliquely incident light, and then the polarization difference in the vertically and horizontally polarized scattered light was computed, from which the submicron particle size distribution was inverted subsequently. Experiments were performed using polystyrene microsphere standard particles with particle sizes of 350 nm, 200 nm, and 100 nm. The experimental results show that (1) the Pearson correlation coefficient of the linearly fitted curve of the corrected polarization difference to the theoretical polarization difference is larger than 0.997, and the slope and intercept of the linearly fitted curve are, respectively, close to 1 and 0, indicating that the corrected polarization difference is highly consistent with the theoretical polarization difference; (2) the mean relative error and coefficient of variation of the particle size distribution parameter D50 obtained from the polarization difference with high angular resolution (angular separation = 2°) are better than those of the parameter D50 obtained from the polarization difference with low angular resolution (angular separation = 12°), indicating better accuracy and repeatability of the particle size distribution inverted from the polarization difference with high angular resolution; and (3) for the particle size distribution parameters D10, D50, and D90 obtained from the scattering angle-corrected polarization difference with high angular resolution, the deviation of the measured values from the average value are all smaller than the thresholds given in the international standard, indicating a good repeatability of the proposed method.

With the rapid development of micro-machining technology, the feature size of object parts becomes smaller whilst the roundness tolerance must be critically verified at sub-micrometers or nanometers. Therefore, establishing a method is critically important for evaluating roundness errors to guarantee the machining quality. A progressive search method is proposed based on the minimum zone criterion in the Cartesian coordinate system in this paper. The least-square center of the measured points is used as the initial reference center by establishing a search circle model for progressively approaching the minimum zone circle center. To testify to the feasibility and performance of the proposed method, comparison and simulation experiments are implemented. The results demonstrated that the progressive search method is effective, reliable, and can evaluate roundness error accurately and quickly with not more than 0.1 s and 10 times.

Plastic recycling is the most effective way to solve plastic pollution. Color recognition of plastic is a key step in the plastic recycling process, which is very important for improving the utilization rate of waste plastic. At present, the manual recognition method is inefficient and cannot meet the requirements of large-scale production, while the existing color recognition based on machine vision has problems such as low recognition accuracy of similar colors, complicated algorithm and high system cost. According to the above problems, a color recognition method based on multi-wavelength transmission spectrum was proposed in this paper for the color recognition of colorless, light blue, light green and apple green transparent plastic. For each transparent plastic, the transmission spectra at 381 nm, 439 nm, 620 nm and white transmission light source were obtained, and the ratios of R, G and B wavebands of the transmission spectra were used to set up a color feature, which was then used for color recognition. A color recognition model was established based on the color features and naive Bayes model. The 10-fold cross-validation results showed that the recognition accuracy of the four colors of transparent plastic reached 100%.

The rice-wheat rotation system is a major agricultural practice in China as well as an important source of greenhouse gas (GHG) emissions. In this study, the developed mid-infrared laser heterodyne radiometer (MIR-LHR) was used for the remote sensing of atmospheric CH₄ and N₂O concentrations above the rice-wheat rotation system. From April 2019 to May 2022, the atmospheric column concentrations of CH₄ and N₂O above the rice-wheat rotation system were continuously observed in Hefei, China. The peak values of the N₂O column concentration appeared 7~10 days after wheat seasonal fertilization, with additional peaks during the drainage period of rice cultivation. During the three-year rice-wheat crop rotation cycle, a consistent trend was observed in the CH₄ column concentrations, which increased during the rice-growing season and subsequently decreased during the wheat-growing season. The data reveal different seasonal patterns and the impact of agricultural activities on their emissions. During the observation period, the fluctuations in the CH₄ and N₂O column concentrations associated with the rice-wheat rotation system were about 40 ppbv and 6 ppbv, respectively. The MIR-LHR developed for this study shows great potential for analyzing fluctuations in atmospheric column concentrations caused by GHG emissions in the rice-wheat rotation system.