基于分布式光纤和贝叶斯模型平均的土石坝土体含水率监测方法研究OA

The Active Heating-Optical Frequency Domain Reflectometry(AH-OFDR)technology provides an effective means for distributed high-spatial-resolution monitoring of soil volumetric moisture content.However,the accurate inversion of thermal response data remains the core challenge restricting its engineering applications.In this study,laboratory AH-OFDR monitoring experiments for soil volumetric moisture content are carried out to clarify the influence laws of various variables on temperature rise.Furthermore,a temperature-moisture content inversion model is constructed based on the Bayesian Model Averaging(BMA)theory,realizing adaptive weight fusion of multi-feature combinations.The experimental results show that:(a)the volumetric moisture content exhibits a significant negative correlation with temperature rise,while the heating power is positively proportional to temperature rise,and the fluctuations in initial temperature have no significant interference with the temperature rise index;and(b)the BMA model constructed in this study achieves a coefficient of determination R2 of 0.84 and a root mean square error(RMSE)of 3.45%for moisture content inversion,and the posterior inclusion probabilities of core variables(reciprocal of temperature rise per unit power,porosity)are close to 1.0,which can adapt to the thermal characteristic heterogeneity under different working conditions.This study can provide reliable methodological support for the distributed accurate inversion of moisture content in engineering scenarios such as seepage monitoring of earth-rock dams using AH-OFDR technology.