Numerical modeling of an automated optical belt sorter using the Discrete Element Method

At - Automatisierungstechnik

et al. 2020

Optical belt sorters are a versatile means to sort bulk materials. In previous work, we presented a novel design of an optical belt sorter, which includes an area scan camera instead of a line scan camera. Line scan cameras, which are well-established in optical belt sorting, only allow for a single observation of each particle. Using multitarget tracking, the data of the area scan camera can be used to derive a part of the trajectory of each particle. The knowledge of the trajectories can be used to generate accurate predictions as to when and where each particle passes the separation mechanism. Accurate predictions are key to achieve high quality sorting results. The accuracy of the trajectories and the predictions heavily depends on the motion model used. In an evaluation based on a simulation that provides us with ground truth trajectories, we previously identified a bias in the temporal component of the prediction. In this paper, we analyze the simulation-based ground truth data of the motion of different bulk materials and derive models specifically tailored to the generation of accurate predictions for particles traveling on a conveyor belt. The derived models are evaluated using simulation data involving three different bulk materials. The evaluation shows that the constant velocity model and constant acceleration model can be outperformed by utilizing the similarities in the motion behavior of particles of the same type.

Section: Experimental Platform and Simulation Methodologymentioning

confidence: 99%

Section: Predictive Tracking For Optical Belt Sortersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Predictive tracking with improved motion models for optical belt sorting

Pfaff

Pieper

At - Automatisierungstechnik

et al. 2020

“…Results presented below were obtained using six datasets. Four of these were generated using a particle-based simulation of an optical belt sorter as described in [20]. Here, the discrete element method (DEM) was employed to accurately model the particle-particle and particle-wall interactions within the sorting system.…”

Section: Setup and Datasetsmentioning

confidence: 99%

“…The name of the dataset describes the type of objects that were applied on the sorting system. For the simulated datasets, detailed information regarding contact forces, etc., is provided in [20]. As can be seen, they strongly differ in terms of included measurements overall as well as per frame.…”

Section: Setup and Datasetsmentioning

confidence: 99%

Real-time multitarget tracking for sensor-based sorting

Pfaff

Wagner

et al. 2017

J Real-Time Image Proc

Utilizing parallel algorithms is an established way of increasing performance in systems that are bound to real-time restrictions. Sensor-based sorting is a machine vision application for which firm real-time requirements need to be respected in order to reliably remove potentially harmful entities from a material feed. Recently, employing a predictive tracking approach using multitarget tracking in order to decrease the error in the physical separation in optical sorting has been proposed. For implementations that use hard associations between measurements and tracks, a linear assignment problem has to be solved for each frame recorded by a camera. The auction algorithm can be utilized for this purpose, which also has the advantage of being well suited for parallel architectures. In this paper, an improved implementation of this algorithm for a graphics processing unit (GPU) is presented. The resulting algorithm is implemented in both an OpenCL and a CUDA based environment. By using an optimized data structure, the presented algorithm outperforms recently proposed implementations in terms of speed while retaining the quality of output of the algorithm. Furthermore, memory requirements are significantly decreased, which is important for embedded systems. Experimental results are provided for two different GPUs and six datasets. It is shown that the proposed approach is of particular interest for applications dealing with comparatively large problem sizes.

Benchmarking a DEM‐CFD Model of an Optical Belt Sorter by Experimental Comparison

Bauer

Chemie Ingenieur Technik

Reith‐Braun

et al. 2022

Dedicated to Prof. Dr.-Ing. Joachim Werther on the occasion of his 80th birthday A DEM-CFD (discrete element method -computational fluid dynamics) model of an optical belt sorter was extensively compared with experiments of a laboratory-scale sorter to assess the model's accuracy. Brick and sand-lime brick were considered as materials. First, the transport characteristics on the conveyor belt, involving mass flow, lateral particle distribution and proximity, were compared. Second, sorting results were benchmarked for varying mixture proportions at differing mass flows. It was found that the numerical model is able to reproduce the experimental results with high accuracy.