Deformation Monitoring Method Based On Inertial Technology

Development and utilization of mineral resources is a double-edged sword, it not only brings material wealth, but also damages to human survival and development environment to some extent, it can cause subsidence as the representative of the geological disaster based on the ground. Therefore, to ensure the sustainable development of mining area, we must adopt advanced technology on monitoring and controlling the ground settlement caused by the subsidence.In order to find out rules and trends of surface subsidence in time and monitor the deformation real-timely and effectively, and then determine the sinking situation of the whole surface movement areas. This paper selects numbers of MIMU, designs distributed network and measurement system, and lays optical fiber as an aided measurement. Thus the results are more comprehensive and intuitive, can provide large amounts of data to estimate parameters determination and analyse the terrain movements.The terrain deformation is caused by ground settlement, this kind of subtle terrain deformation signal cannot be directly adopted MIMU calculating attitude angles to determine the deformation due to the special nature of their own conditions, small subsidence range, slow deformation changes. This paper presents a piecewise model of multidimensional time series indirect deformation prediction method based on inertial measurement parameters.The data that collect by MIMU measurement unit has the characteristics of time series such as high dimension, complexity, dynamic and high noise. Firstly,deformation prediction is filtered after compensation analysis by Wavelet and Wavelet Transform theory, and then establish model of time series by using the Kalman filtering algorithm for processing the random error. Secondly, we use similarity calculation in every period of time sequence to predict the deformation trend of deformable body. Use the actual collection data to simulation. The result shows that the deformation prediction method presented in this paper is correct and effective, and can be applied to predict the practice of deformation.