The vision-based automatic systems for in-line detection, identification, and separation are widely used in the industry, and it is difficult for such systems to achieve a simplified structure, high speed, high efficiency, and integrated coordinated control. Taking the dual-energy x-ray transmission solid waste high-speed sorting line as an example, an automatic control system was proposed, integrating data reading, image processing, sequential logic control, communication, and human–machine interface based on a personal computer with a general operating system. The hardware platform was introduced, and the design principles of operation parameters were investigated. The software was developed in C language with Microsoft Visual Studio 2012. The multi-core multi-thread technology has been utilized in which the optimized process-thread settings (OPTS), first-in first-out (FIFO) stacker, variable sharing between threads, and encoder position synchronization were employed. The whole system was experimentally verified at the line speed of 1 m/s. The results showed that the average scan cycle of sequential logic control was only 15 µs, which could fully ensure the real-time high-speed logic control and accuracy of position synchronization, OPTS improved the stability and disturbance rejection, FIFO stacker and variable sharing between threads was adapted to the realistic buffer materials, the encoder position synchronization avoided the accumulation of measurement errors, and the main operations run in parallel and coordinately and were suitable for the high-speed separation of multiple columns of irregular materials. The presented control system has the advantages of near real-time, high speed, high efficiency, low cost, easy reconstruction, and capability to manage and control integration and has a good practical application value.

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.

With their wide application in industrial fields, the denoising and/or filtering of line-scan images is becoming more important, which also affects the quality of their subsequent recognition or classification. Based on the application of single source dual-energy X-ray transmission (DE-XRT) line-scan in-line material sorting and the different horizontal and vertical characteristics of line-scan images, an improved adaptive Kalman-median filter (IAKMF) was proposed for several kinds of noises of an energy integral detector. The filter was realized through the determination of the off-line noise total covariance, the covariance distribution coefficient between the process noise and measurement noise, the adaptive covariance scale coefficient, calculation scanning mode and single line median filter. The experimental results show that the proposed filter has the advantages of simple code, good real-time control, high precision, small artifacts, convenience and practicality. It can take into account the filtering of high-frequency random noise, the retention of low-frequency real signal fluctuation and the preservation of shape features. The filter also has a good practical application value and can be improved and extended to other line-scan image filtering scenarios.