After the mining subsidence area reaches the stable state of surface movement, due to the continuous existence of the mutual extrusion and activation state between rock strata, the movement of particles, rock creep, and soil compression will affect the surface movement in the long-term stability, thereby threatening the safety and stability of the above ground buildings. In order to study the deformation law of rock strata movement and surface displacement after the mining subsidence area is stabilized, establish a ground deformation model caused by mining, explore the characteristics of ground movement and deformation under the action of building loads, design a similar material simulation experiment, record the ground movement changes within 378 days after the mining is completed, after the settlement is stabilized, apply equivalent loads of 10–30 floors to the model at different locations, and study various surface deformation data, Analyze the change rule. In order to quantitatively analyze the impact of residual deformation of goaf on buildings under building load, the D5 gate area of Tangshan World Horticultural Exposition in mining subsidence area is taken as an example to calculate the ground settlement value and other deformation data using probability analysis method, and the Kelvin model in rock mechanics is introduced in terms of the duration of residual deformation. The calculation results are close to the actual measured values, and the impact of residual deformation on the proposed building is analyzed.
Introduction: In the coal mining process, the intense mining pressure is an important factor hindering the safe and efficient production of the working face. In severe cases, it causes deformations in roadways such as roof breakages and rockbursts, and leads to instability. This can result in the roof falling over a large area and the coal wall, thereby inducing dynamic disasters. These aspects have restricted the economic benefits of coal.
Methods: In this study, we set four model limitations based on the limited scope of action of the mining pressure itself and the quantitative relationships between mining pressures in different regions. A multiple linear regression model with these limitations is proposed for predicting the mining pressure for preventing roof breakages and rockbursts. Based on a hydraulic support monitoring dataset from a fully mechanized caving face of coal mining, the mining pressure prediction model is trained by using the first 70% of the dataset. And the linear regression coefficient of the model and the predicted value of the mining pressure are obtained. Then, the last 30% of the dataset was used for the validation of the model.
Results: The research results show that the constrained multiple linear regression model can achieve remarkable prediction results. According to predictions of tens of thousands of on-site mining pressure datasets, the predicted data and actual pressure data have the same change trend and maintain a low relative error.
Discussion: Therefore, after real-time mining pressure monitoring, the system obtains the roof pressure of the fully mechanized mining face. According to the dataset, the proposed prediction model algorithm quickly predicts the roof pressure value of the next mining section and effectively forewarns roof breakages and other accidents.