Correlation Analysis of Flocculation Detection and Control Parameters Based on Multi-target Tracking

Dynamic optimization of coagulation dosage is one of the most crucial processes in water treatment. As the demand of effluent turbidity is getting higher and higher, the control performance of traditional approaches like SCD and FCD are not satisfactory and stable with the influence of raw water quality and control parameters. This paper proposes an multi-target tracking-based detection system that integrates image analysis and processing, Kalman filtering, MHT and other algorithms, to solve the key issues like floc image acquisition and detection in coagulation and flocculation process, extraction of floc characteristics and the automatic optimization control of coagulation dosage. Experimental results show that: the detection model based on multi-target tracking fully reveal a good correlation between the floc settling velocities and sedimentation turbidity, provide a basis for the automatic optimal control of coagulant dosage.