Enhanced pneumatic ejection for metal sorting and recycling
Başlık çevirisi mevcut değil.
- Tez No: 912521
- Danışmanlar: PROF. DR. JEF PEETERS, DR. BART ENGELEN
- Tez Türü: Yüksek Lisans
- Konular: Belirtilmemiş.
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2022
- Dil: İngilizce
- Üniversite: Katholieke Universiteit Leuven (Catholic University of Leuven)
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 152
Özet
Non-ferrous metals can be classified based on information of multiple techniques, such as eddy current, LIBS, XRT and optical sorting. Once the material is classified the most commonly adopted technique for sorting is pneumatic ejection mechanisms. The energy consumption of such a system can be as high as 11kW the purity and capacity of automated sorting systems is to a large extend determined by the sorting efficiency of the pneumatic ejection system. Therefore, this research focuses on the development of an enhanced control for the pneumatic ejection system using information from the vision system, such as weight, area, length and width. The enhanced control includes the varying of the opening duration of the valves and the number of valves opened. Prior research performed by others showed that the parameters ,such as speed of the conveyor belt, position and angle of the nozzles of the pneumatic ejection system affect separation distance between aluminum and copper pieces. This research uses a different position for the pneumatic ejection system and focuses on distance covered by aluminum pieces only, the duration and timing of the valves. An Intel RealSense camera is used to capture the trajectory of an ejected piece. Utilizing the snap7 library, the control of the opening duration and number of the valves were integrated with tracking system. A python script that allows a metal piece to be exposed to 7 different valve opening durations that range between 2-14 ms was written. Each valve opening duration was repeated 3 times resulting in a total of 21 ejections for one metal piece. A total of 27 mixed twitch aluminum pieces were tested resulting in 567 ejections. 3D images taken by Lidar L515 camera are used to extract geometrical parameters of the 27 metal pieces that are selected based on shapes, such as flat, bulky and long. The weights and the geometrical parameters obtained, such as width, length, area and weight, were used to classify the metal pieces as either bulky, flat or long. Although the metal pieces were manually positioned in the same manner on a conveyor with a constant belt speed and that the time between the triggering of the optical sensor and the activation of the pneumatic valves was experimentally determined for every piece, obtained results indicate that multiple ejections failed. After further reflection the main reasons for this are assumed to be high fluctuations in the distance for a fixed valve opening duration due to non-repeatable orientation of a piece on the belt and non-homogenous surface of the belt affecting the moment and the way a piece falls from belt. Although 24 out of 27 pieces have best-fit lines with a positive slope describing the relationship between horizontal distance and valve opening time, three-way sorting is not feasible due to the failing ejections decreasing the accuracy and efficiency for a target distance. The air consumption can be reduced by limiting the valve opening duration to 14ms while causing at least 750 mm horizontal motion for 22 pieces which can represent 63.5% of twitch aluminum waste stream (40-120mm). Reducing valve opening duration to 14ms and the number of active nozzles to the average width of twitch aluminum waste stream results in a yearly cost of 5234 euros that represents the 63.5% of waste stream for a machine that processes 4 ton/h (6800 hours yearly) . A point mass is calculated to spend 624 ms between sensor detection spray center-line, and is referred to as theoretical countdown time. Countdowns for each of the 27 pieces are tested experimentally. The highest deviation from the theoretically calculated value is 94 ms. Longer pieces with mass centers further away from the end-detection tend to have more deviation from the theoretical countdown value.
Özet (Çeviri)
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