Title :
Self-Adaptive Seismic Signal Collection Recording System Based on ARM
Author :
Gao, Meijuan ; Xu, Jin ; Tian, Jingwen
Author_Institution :
Beijing Union Univ., Beijing
Abstract :
Aim at the traditional natural seismic signal collection system has disadvantage of narrow wave band and data collection quantity is too large, a self-adaptive seismic signal collection recording system based on ARM (advanced RISC machines) is presented in this paper. The MEMS acceleration sensor chip with the characteristic of good low-frequency response and high sensitivity is used to detect seismic signal, and amplifying and filtering circuit are designed for signal conditioning to increase the signal noise ratio (SNR). Then the whole detection circuit will be assembled reasonably and debugged, and the three component seismograph is designed. A threshold signal will be set in the software to confirm the start and end time for recording system, in order to achieve the data collection efficiency and high reliability.
Keywords :
geophysical signal processing; reduced instruction set computing; seismology; seismometers; signal processing equipment; ARM; MEMS acceleration sensor chip; advanced RISC machines; seismograph; self-adaptive seismic signal collection recording system; signal conditioning; signal noise ratio; Acceleration; Circuit noise; Filtering; Low-frequency noise; Micromechanical devices; Reduced instruction set computing; Sensor phenomena and characterization; Signal design; Signal detection; Signal to noise ratio; ARM; Collection; Seismic signal;
Conference_Titel :
Embedded Computing, 2008. SEC '08. Fifth IEEE International Symposium on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-3348-3
DOI :
10.1109/SEC.2008.27
