Computer vision system for froth-middlings interface level detection in the primary separation vessels

Abstract Bitumen from the surface-mined oil sands is separated through a water-based gravity separation process in the Primary Separation Vessels (PSV). The froth-middlings interface level in the PSVs is the most important control variable in the process. Bitumen recovery and downstream operations are critically dependent on the interface level measurement and control. In this paper, we describe a robust computer vision system that uses image and data processing techniques to estimate the froth-middlings interface level. The algorithm in the computer vision system processes the online video frames of a camera mounted to the PSV sight glasses, and it is based on a combination of static and dynamic image processing steps. Industrial results show that the computer vision algorithm is more accurate and reliable when compared to the other instruments, as well as robust against process and environmental abnormalities.