Abstract: Efficient treatment of coal slurry water is a key link in coal cleaning and processing process. The problem currently encountered in treatment of coal slurry water is that addition of agents cannot be accurately controlled during the slurry settling process. To tackle the problem, the method for recognition of turbidity of clarified layer of coal slurry water using video frame-splitting processing and YOLO algorithms is proposed. For testing the effectiveness of the proposed method, videos of the slurry water samples with a turbidity in a range of 100~1,000 NTU are splitted into 900 images, the dataset of which are then divided randomly into training and validation sets according to a ratio of 9∶1 using frame-splitting algorithm and labeling data annotation tool. Following that, the open-source YOLOv5m.pt preweighted training model of YOLOv5 algorithm is used to train the training set. Through setting IOU, confidence level and number of training rounds, and with loss function, accuracy and recall rate as evaluation indicators, the model classification performance is assessed based on confidence level of the detected results. As indicated by study results, the loss ratio of the recognition algorithm keeps decreasing at first and then stay stabilized at 0.01 during the training process; the accuracy of recognition for samples at different level of turbidity tends to rise continuously from about 0.1 to 0.98 while the recall rate is seen to go up to continuously to 0.99, with an optimum confidence level being as high as 0.98; the algorithms used demonstrate a remarkably good effect for recognition different turbidities and certain adaptability and generalization capabilities as well; and for detection of the same turbidity, the accuracy is relatively stable with a good robustness, well demonstrating the accuracy and stability of the algorithms. The research-derived achievements provide new ideas for dynamic detection of turbidity of coal slurry water and a valuable reference for making intelligent transformation of coal slurry water treatment system.