DocumentCode :
2691287
Title :
Application of Coriolis Mass Flowmeter Based on Modified BPNN Algorithm in Monitoring Mine Water Inrush
Author :
Wei, Min-Hong ; Zhao, Yong ; Tong, Min-Ming
Author_Institution :
Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
fYear :
2012
fDate :
7-9 July 2012
Firstpage :
257
Lastpage :
260
Abstract :
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 accurately 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.
Keywords :
Coriolis force; backpropagation; computerised monitoring; field programmable gate arrays; flowmeters; interference suppression; mining; neural nets; signal processing; BPNN algorithm; CMF system; FPGA; STM32; accurate monitoring; conventional CMF secondary instrument; coriolis mass flowmeter; density data; flow signal; fluid density; frequency data; interference; mine water inrush monitoring; phase difference data; phase frequency property; precision detection; real-time monitoring; signal processing system; temperature data; train network; training samples; zero-drift; BP neural network; CMF secondary instrument; Seam floor; waterinrush;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Measurement, Control and Sensor Network (CMCSN), 2012 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4673-2033-7
Type :
conf
DOI :
10.1109/CMCSN.2012.62
Filename :
6245829
Link To Document :
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