Simulation of Data Processing Model of Optical Fiber Sensor for Dynamic Monitoring of Mineral Resources Reserves

The purpose of dynamic monitoring of mineral resources reserves is to grasp the data of mineral resources reserves mined, lost and held by all mining enterprises nationwide in the current year in real time and accurately, to understand the changes and reasons of mineral resources reserves of various mining enterprises, to effectively protect and rationally utilize mine mineral resources, and to provide basic information for mining administration. In this paper, an OFS (optical fiber sensor) data processing model for dynamic monitoring of mineral resources reserves is established. On the basis of systematically expounding the principle of DOFS (Distributed OFS) system, the denoising algorithm based on wavelet packet is applied to the preprocessing of optical fiber acquisition signals. This paper designs a data processing system based on DSP (Digital Signal Process), which consists of high-speed AD, DSP module based on FPGA (Field Programmable Gata Array), USB2.0 transmission module and computer. Wavelet packet denoising algorithm is applied to the denoising of DOFS data, which improves the signal-to-noise ratio of optical fiber sensor network data. The research results show that using wavelet packet to denoise the experimental data collected by DOFS positioning system has obvious effect. The dynamic monitoring system designed in this paper breaks the dependence of the traditional dynamic monitoring system on the base station and improves the monitoring accuracy of dynamic monitoring reserves.