Multi-Scale Model Of Dam Safety Condition Monitoring Based On Dynamic Bayesian Networks
Fang Weihua, Lanyu Xu · Intelligent Automation & Soft Computing · 2012
Abstract In order to monitor dam safety condition better, a Dynamic Bayesian Networks (DBN) model is developed to overcome the shortcomings of the ordinary monitoring methods in this paper. Ordinary methods include comprehensive assessment methods and numerical simulation methods. Comprehensive assessment methods have shortcomings such as weight detemunation, scale difference, variables correlation, etc. In addition, comprehensive assessment methods cannot describe the multi-scale characteristics of monitoring data and dynamic property of large dam. Numerical simulation methods need complex mathematical theory, mechanics methodologies and high performance computer. DBN is a novel model with the consideration of correlations, delay and multi-scale characteristics of the variables such as deformation, seepage, stress and water load and temperature loads, as well as duration at every state. And the new model is also a simpler method with less experience, computational complexity and fewer experiments compari...