Computer vision based interface level control in a separation cell

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.