Research on Dam Grouting Efficiency Based on Dynamic Detection and Prediction of Cement Slurry Rheology

Grout is an essential working fluid in building finish and the properties of grout influence the finish quality and engineering cost directly. How to test rheological property of grout quickly, accurately and comprehensively is a problem that needs to be solved. This paper aims to study the rheological properties of the grouting fluid, design the dynamic continuous and accurate measurement of the rheological parameters, and predict the rheological model through the upper computer. The specific research includes the following three aspects: (1) Based on the rheological theory of solid-liquid two-phase flow fluid, analyze the critical parameters of cement slurry rheology and its influencing factors, and establish a calculation and analysis model for the detection of the rheological parameters of the inner cylinder rotary. (2) We design a micro-torque detection scheme and signal measurement circuit, build the overall mathematical model for dynamic detection of slurry rheological performance, and realize the dynamic and accurate detection of slurry under different shear rates. (3) Aiming at the flow characteristics of slurry with different water-cement ratios, a prediction model of rheological properties based on the BP neural network is established to guide the detection and analysis of the rheological properties of grouting slurry at the base of dams.