The application relates to a
sediment particle dynamic detection method and a detection
system, and relates to the technical field of
river sediment detection technology. The method comprises the following steps: S1, obtaining a high-pressure
sediment sample, performing metering, and then performing
pressure reduction treatment to form a to-be-detected sample; S2, screening the to-be-detected sample according to particle size to form a first sample and a second sample; S3, performing
turbidity detection and
dilution on the sample by using a transmission-scattering
ratio method; S4, irradiating the first sample with multi-
wavelength combined shaping light, and obtaining particle morphology and component information based on
parameter analysis; S5, performing imaging detection on the second sample, obtaining a polarization image and a
spectral image, and fusing and analyzing the polarization image and the
spectral image to obtain particle morphology and component information; and S6, integrating detection data, identifying and classifying through a
machine learning model, and outputting a detection result. Through the steps of high-pressure sampling,
pressure reduction, particle size screening,
turbidity detection and
dilution, double-channel detection and
data integration, the labor intensity is reduced, and the detection efficiency is improved.