In this paper, conventional CMF secondary instrument is improved by embedding modified BPNN algorithm for real-time and accurate monitoring water inrush in mine. The data of frequency, temperature and phase difference determined by CMF is applied to train network, as a result, phase frequency property of flow signal may be analyzed precisely for measuring accurately fluid density and mass flow of water inrush. The signal processing system of CMF secondary instrument based on FPGA, STM32 and BPNN is designed to eliminate interference and zero-drift. Trial result in simulated mine water inrush illustrates that data of mass flow and density chosen as training samples of BPNN can be measured more accratelly than that not chosen as training sample, detect precision is improved and influence of temperature on CMF system is eliminated basically, this design offers the basis for real-time and accurate monitoring water inrush in mine.
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