High-Precision Dynamic Subsidence Prediction Model Aided by Field Measured Data

"China is the largest producer and consumer of coal in the world. The mining-induced surface subsidence has bad influences on the surface and structures above the surface. In order to minimize disasters, removal, reinforcement, or maintenance structures are often adopted. In the application of maintenance methods, it is necessary to carry out dynamic surface subsidence prediction to choose maintenance methods, optimize maintenance time, and evaluate the amounts of work. Time series methods and influence function methods are common for dynamic surface subsidence prediction, but the former is difficult to consider with underground mining conditions, and the latter has low prediction precision. Therefore, this paper develops a dynamic subsidence prediction model aided by field-measured data and realizes the model programming. The model could achieve high-precision prediction of dynamic surface deformation through optimizing the parameters in time by using field-measured data of surface subsidence. The research results of engineering cases show that, with the method of dynamic prediction, the standard error can be controlled in the range of 5%, greatly improving the accuracy of dynamic prediction of mining subsidence, which provides strong technical support for the maintenance and management of structures. INTRODUCTION With the rapid economic development and continued industrialization process, the demand for energy is growing in China. Today, China is one of the largest coal, oil, and gas consumers in the world. Coal consumption accounts for 47.7% of the total consumption in the world (Tian, 2016). In order to meet the demand for coal resources in the process of modernization, more and more coal mines carry out coal mining under villages, buildings, highways, and bodies of water. The mining-induced overlying strata and surface subsidence have bad effects on surface and on various structures (such as buildings, railways, highways, high-tension transmission lines) and could even cause various disasters (Williams et al., 1998; Bell et al., 2000; Doyle et al., 2002). Generally, methods, such as removal, reinforcement, or maintenance are taken to eliminate the adverse impacts (Kraatz, 1984; Bell and Genske, 2001; Wang, 1989). When reinforcement or maintenance is selected to remove bad effects, the proper maintenance methods must be chosen. In addition, maintenance time, as well as an evaluation of time it will take to do the work are necessary to predict the surface subsidence with high precision."