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Computer vision based interface level control in a separation cell

机译:基于计算机视觉的界面电平控制在分离单元中

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Bitumen extraction from oil sands is the core process in the production of oil from oil sands. This floatation process is carried out in large vessels called separation cells. Optimal control of the interface between Bitumen froth and Middlings in these cells can result in a significant improvement in Bitumen recovery and increase process efficiency downstream, resulting in large economic benefits. The major impediment in the implementation of such a control system is the lack of safe and reliable sensors for interface level detection. Traditional instruments such as nuclear gauges, capacity probes etc. are either unsafe or do not give reliable estimates. This work describes a novel sensor for interface level detection, developed using computer vision techniques on video frames captured from a sight glass camera. Specifically, State-space model based Particle filtering is used to provide estimates of the interface level and its quality. It is shown that the algorithm is robust to lighting changes and process abnormalities. Industrial results show highly improved control performance when estimates of the sensor are used for feedback control.
机译:来自油砂的沥青提取是油砂生产油的核心过程。该浮选过程在称为分离细胞的大容器中进行。在这些细胞中沥青泡沫和中间体之间的界面的最佳控制可能导致沥青回收率的显着改善,并提高下游过程效率,导致经济效益很大。实施此类控制系统的主要障碍是缺乏用于接口电平检测的安全可靠的传感器。传统仪器如核仪表,容量探针等要么不安全,要么不提供可靠的估计。这项工作描述了一种用于接口电平检测的新型传感器,使用从看线玻璃相机捕获的视频帧上的计算机视觉技术开发。具体地,基于状态模型模型的粒子滤波器用于提供界面电平及其质量的估计。结果表明,该算法对照明变化和处理异常具有鲁棒性。当传感器的估计用于反馈控制时,工业结果显示出高度改善的控制性能。

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