## 3 Results and Discussion
### Center-of-Gravity Coordinates Calculation
It uses part of the morphological features to calculate the mass and center-of-gravity coordinates and employs gas-ejection to realize in-line multicategory scrap identification and separation with one measurement. It is not affected by the previous shredding processes and equipment, though its overall identification accuracy by count basis is slightly lower than 90% compared with that from the method adopted by [PERSON] et al. [6]. It has strong material adaptability due to less influence from the thin layer contamination of the material surface, compared with color sorting [4], XFR [13] and LIBS [14]. It is closer to the practical engineering application than the methods of heat conduction [35] and magnetic induction [15; 19]. The initial investment of this method is relatively higher than that proposed by [PERSON] et al. [6] or the color-sorting method; however, it has higher efficiency and lower long-term operation costs, due to multiple sorting at one measurement. The method cannot make sorting of different aluminum alloys such as Alc and Alw more refined as reported by [PERSON] et al. [6], Delft University of Technology [5] and [PERSON] et al. [19], which is mainly caused by the sole relationship between DE-XRT and \(Z\). For further sorting, it is necessary to measure and acquire other physical properties including density, electrical conductivity, magnetic permeability, mechanical properties, etc., whereas the methods in the above literature all combine more than two kinds of sensors, which can make the sorting refined. There are several problems in our method to be further solved. For example, the material calibration required in the method leads to high costs in time and work. The resolution of the detector, the differences in the scintillators and their processing units, cross-talk noise, and random X-ray noise have a great influence on the recognition accuracy. In addition, there are many challenges for the identification of materials with close atomic numbers. For example, it is still difficult for industrial realization of large-scale identification and classification between Al and Mg, and between Cu, brass and SS. Therefore, enough effective points in the material range, good filtering, intelligent algorithms and equipment accuracy will be particularly important factors. The simulation study on the control of gas-ejection falling point was conducted and the optimal ejection elevation angle was 40\({}^{\circ}\), which can be seen in Reference [4]. The control of the falling point of variable gas-ejection may be affected by such factors as the ratio of shape characteristics of the material, mean thickness to area, the relationship between compressed gas pressure and time, air resistance, shape and diameter of nozzles, the opening and closing process of high frequency valves, etc. Because FLUENT simulation and related actual experiments are in progress, this paper is only for theoretical proof. Meanwhile, with respect to materials with overexposure and underexposure that need secondary sorting, the variable X-ray energy and recalibration with the same method in this paper can be taken into account, so as to further expand the sorting range, which is worthy of further research and experiment. For example, for secondary sorting, a reduction of tube voltage or tube current could be used for overexposed materials while an increase in the tube voltage or tube current should be considered for underexposed materials. Furthermore, an improvement in the adjustment range of the tube voltage and tube current of the X-ray source and the resolution of the detector could further expand the sorting range and facilitate the research into variable X-ray energy.