Research on Sediment Particle Size Distribution Based on K-means Clustering and Prewitt Operator

Sediment particle size distribution is a key parameter for studying the laws of sediment transport.Traditional particle size measurement methods suffer from being time-consuming and operationally complex.To enhance measurement efficiency,this paper proposes an image segmentation method combining K-means clustering and Prewitt operator for the rapid measurement of suspended sediment particle size.This method achieves separation between the background and particles through grayscale clustering,and extracts particle boundaries for equivalent particle size conversion.Experiments were conducted in an indoor grid-generated turbulence device,targeting suspended particles within the size range of 10~100μm.We compared the image-based method with a Malvern laser particle size analyzer.The comparison shows that the maximum relative error in median particle size between the two methods does not exceed 12%,indicating good real-time performance and measurement accuracy,and confirm the validity of the image-based method.This method offers a low-cost and efficient solution for online monitoring of sediment particle size.