Combination of Dual-Energy X-ray Transmission and Variable Gas-Ejection for the In-Line Automatic Sorting of Many Types of Scrap in One Measurement

Abstract

As an important part of pretreatment before recycling, sorting has a great impact on the quality, efficiency, cost and difficulty of recycling. In this paper, dual-energy X-ray transmission (DE-XRT) combined with variable gas-ejection is used to improve the quality and efficiency of in-line automatic sorting of waste non-ferrous metals. A method was proposed to judge the sorting ability, identify the types, and calculate the mass and center-of-gravity coordinates according to the shading of low-energy, the line scan direction coordinate and transparency natural logarithm ratio of low energy to high energy (R_value). The material identification was satisfied by the nearest neighbor algorithm of effective points in the material range to the R_value calibration surface. The flow-process of identification was also presented. Based on the thickness of the calibration surface, the material mass and center-of-gravity coordinates were calculated. The feasibility of controlling material falling points by variable gas-ejection was analyzed. The experimental verification of self-made materials showed that identification accuracy by count basis was 85%, mass and center-of-gravity coordinates calculation errors were both below 5%. The method proposed features high accuracy, high efficiency, and low operation cost and is of great application value even to other solid waste sorting, such as plastics, glass and ceramics.

Improved Adaptive Kalman-Median Filter for Line-Scan X-ray Transmission Image

“…In contrast, the horizontal-vertical bidirectional average scanning mode in Figure 7e has a good overall filtering effect, which shows that: (i) it has good smoothness; (ii) no obvious translation or staggered lines are found in the internal image of the material; (iii) it also has a certain filtering effect on local crosstalk noise. According to another calculation method of our research work [29], the center-of-gravity coordinates (unit: pixel) that are calculated in Figure 7a-e lines are found in the internal image of the material; (iii) it also has a certain filtering effect on local crosstalk noise. According to another calculation method of our research work [29], the center-of-gravity coordinates (unit: pixel) that are calculated in Figure 7a-e The filtering effects of different calculation scanning modes are mainly reflected in filtering accuracy, filtering smoothness and the artifacts of image movement, dislocation and deformation that are caused by signal following.…”

“…According to another calculation method of our research work [29], the center-of-gravity coordinates (unit: pixel) that are calculated in Figure 7a-e lines are found in the internal image of the material; (iii) it also has a certain filtering effect on local crosstalk noise. According to another calculation method of our research work [29], the center-of-gravity coordinates (unit: pixel) that are calculated in Figure 7a-e The filtering effects of different calculation scanning modes are mainly reflected in filtering accuracy, filtering smoothness and the artifacts of image movement, dislocation and deformation that are caused by signal following.…”

“…An Advantech (Taiwan, China) IPC-610MB-L industrial PC (personal computer) acts as the host computer with a 16 GB RAM (random access memory) and Windows 7 software, Microsoft Visual C++ 2012, as well as a MATLAB R2020a, which has an Intel i7-2600, 4-core, 64-bit, and 3.4 GHz CPU (central processing unit). The composition of the system and the relationship of various operating parameters were described in detail in our other two research works [28,29].…”