[Study on the Distinguishment of Camouflage Paints Based on Depolarization Characteristics].

As an important part in the modern warfare, camouflage technology plays a critical role in the battlefield, and the results of detection of camouflage target directly affect the results of war. However, there is little paper to detect camouflage paint by depolarization characteristics, so it is of great significance to use the depolarization technology to study the distinguishment of camouflage paints. To address this issue, we studied the mechanism of the scattering of electromagnetic wave, and analysed the relationship between the characteristics of depolarization and mechanism of scattering. Jones Matrix and Mueller Matrix were used to set up the physical model, and the Mueller-Jones Matrix was decomposed with the characteristics of polarization, then the depolarization coefficients(ωd) of the surfaces of the samples was acquired. In this experiment, we measured soil and three kinds of camouflage yellow paints in seven different incident angles to analyze the characteristics of depolazation of the soil and three kinds of camouflage yellow paints' surfaces. Finally, we applied the theory of Fresnel formulas to verify the theoretical model. The results showed that: the depolarization coefficients of the samples' surfaces were related to the scattering, and with the increase of the incident angles, the depolarization coefficients were decline. But in the whole measurement process, the depolarization coefficients of the soil were far above the camouflage paints'. Research indicated that: this article was the first paper which used the depolarization coefficients as an important parameter to identify the camouflage targets, and could identify the camouflage yellow paints in the soil-background accurately and effectively. The processes of the experiments were simpler, and the time was shorter. In modern battlefield, it could identify the camouflage targets quickly and easily, and furnish the precious time for the victory of the war. Therefore, the depolarization technology had a great application value, and the paper had very important significance on the development of camouflage recognition technology.

Temperature prediction of ultrasonic vibration-assisted milling.

Machining temperature is a key factor in ultrasonic vibration-assisted milling as it can significantly influence tool wear rate and residual thermal stresses. In current study, a physics-based analytical predictive model on machining temperature in ultrasonic vibration-assisted milling is proposed, without resorting to iterative numerical simulations. As the tool periodically loses contact with the workpiece under vibration, three types of tool-workpiece separation criteria are first examined based on the tool trajectory under ultrasonic vibration. Type I criterion examines whether the relative velocity between tool and workpiece in cutting direction is opposite to the tool rotation direction. Type II criterion examines whether the instantaneous vibration displacement in radial direction is larger than instantaneous uncut chip thickness. Type III criterion examines whether there is overlap between current and previous tool paths due to vibration. If no contact, the instantaneous temperature rise is zero. Otherwise, the temperature rise is predicted under shearing heat source in shear zone and secondary rubbing heat source along machined surface. A mirror heat source method is applied to predict temperature rise, considering oblique band heat sources moving in a semi-infinite medium. The proposed predictive temperature model in ultrasonic vibration-assisted milling is validated through comparison to experimental measurements on Al 6063 alloy. The proposed predictive model is able to match the measured temperature with high accuracy of 1.85% average error and 5.22% largest error among all cases. Sensitivity analysis is also conducted to study the influences of cutting and vibration parameters on temperature. The proposed model is valuable in terms of providing an accurate and reliable reference for the prediction of temperature in ultrasonic vibration-assisted milling.

[Spectral response analysis of offshore thin oil slicks].

Hyperspectral data of thin oil slicks have some spectral response characteristics, and an experiment of offshore thin oil slicks was designed to measure and analyze their reflectance by using ASD hyperspectral instrument. With the oil slick thickness changing, its color varied from rainbow sheen slick to fuchsine sheen slick, kelly sheen slick, aqua sheen slick, silver sheen slick and light sheen slick. The result suggested that different thin oil slicks have different characteristics, some thin oil slicks could change the reflectance at 440 nm which is the spectral absorption peak value of chlorophyll, and the best hyperspectral band to distinguish the different offshore thin oil slicks is located in the range between 350 and 440 nm. The reflectance of thin oil slicks is higher than that of seawater in the hyperspectral data range from 440 to 900 nm, but has no absorption or reflection characteristics compared to seawater's. It could not be detected in the range of near infrared from 900 to 2,500 nm of offshore thin oil slicks because of high noise, low signal and influence of the atmosphere. Finally, the spectral response theory of offshore thin oil slicks was analyzed, and the results indicated that the interference phenomenon of offshore thin oil slicks could add reflected light and change the reflectance of seawater, hence, increase the feasibility of offshore oil slick remote sensing.