Multi-target tracking-based detection of floc settling velocity

摘要

In the automatic control of coagulant dosage in water plant, the final control performance mainly depends on the chosen of control parameters. In this paper, a multi-target tracking-based detection system for floc settling velocity is proposed. The system collects floc dynamic change images online by using an underwater image sensor, and transmits the images to computer image processing system. Therefore the flocs characteristics and their settling velocities will be calculated through image processing and multi-target tracking. Finally, extraction and analysis of floc feature characteristics can be achieved. The system uses Kalman filter and multiple hypothesis tracking (MHT) algorithms to calculate the flocs settling velocities. Weighted average floc settling velocity can be calculated by weighted mathematical statistics. Experimental results show that using of detection system can reflect the floc sedimentation status underwater, and average floc settling velocity is within 0.08 ∼ 0.140 mm/s. This system provides an effective control parameter, floc settling velocity, for the automatic control of coagulant dosage.