Abstract: At present, there is a lack of effective online detection methods for important parameters such as mineral composition that affect the flocculation and sedimentation effect of slime water. There are also lagging issues in the turbidity and interface of the overflow of the concentration tank, which limits the development of intelligent dosing for slime water in coal preparation plants. In order to solve the above problems, a fast detection method for slime water flocculation and sedimentation rate based on image grayscale recognition is proposed. Using a CCD camera to collect images of the sedimentation process of slime water online, and using the mean filtering method for noise reduction, the average grayscale and average grayscale change rate of the image are calculated. The sedimentation rate is obtained by using the relationship between the sedimentation rate and the average grayscale change rate. The method extracts feature values such as grayscale, energy, contrast, variance, and cross-correlation from images through flocculation sedimentation experiments for analysis and verification. The analysis results show the following points. ① Among the five image features, the change in grayscale mean conforms to the variation law of sedimentation rate during the sedimentation process of slime water batches. There are buffer zones, linear zones, and stable zones, and the variation features can be obtained within 30 seconds. ② There is a good linear correlation between the average grayscale change rate and sedimentation rate. When the concentration of slime water is 20 g/L, the linear correlation coefficient between the average grayscale change rate of the image and sedimentation rate under different flocculant addition amounts is 0.977 2. Under the conditions of slime water concentration of 5-25 g/L and flocculant addition amounts of 0.1-0.2 kg/t, the linear correlation coefficient between the two is 0.944 1. ③ The average grayscale change rate can adapt to the changes in the flocculation and sedimentation state of slime water within a large range. The average grayscale change rate can be used to quickly detect the flocculation and sedimentation rate of slime water and serve as the basis for intelligent adjustment of slime water dosing.