Research on Micro-Electro-Mechanical-Systems digital geophone

Xiaodan Zhang Institute of Automation &

Information Engineering, Xi’an University of Technology Xi’an 710048, P.R.China

xinda0723@126.com

Xizheng Ke Institute of Automation &

Information Engineering, Xi’an University of Technology Xi’an 710048, P.R.China

xzke@xaut.edu.cn

Zhiyu Zhang Institute of Automation &

Information Engineering, Xi’an University of Technology Xi’an 710048, P.R.China

zhang_zhiyu2001@yahoo.com.com

Abstract—Geophone is a special purpose sensor which can translate the mechanical vibration into the electrical signal. Micro-Electro-Mechanical Systems (MEMS) digital geophone is the one of the most advanced geophones at present. This paper researches on the internalstructure of MEMS digital geophone and its working principle, and then a close circuit system of MEMS digital geophone is build according to the performance analysis experiments. The simulation results show the effectiveness and feasibility of the build MEMS digital geophone’s close circuit system.

Keywords- mechanical vibration; electrical signal; Micro-Electro-Mechanical Systems (MEMS); digital geophone; close circuit

I. INTRODUCTION

MEMS technology, which is a new science subject, is developed on the micro-electronics, and it is a frontier technology based on the micrometer (mm) and nanometer (nm). MEMS can integrate the mechanical component and electric control system into one unit microsystem [1, 2]. MEMS technology is applied to Geophysics in recent years, which is mainly used in the geophone. Geophone is the most important tool of seismic data acquisition, and its development direct influence the accuracy of the exploration.

II. TYPE STYLE AND FONTS

A. MEMS sensor MEMS digital geophone is composed of MEMS sensor

and Integrated Circuit (IC) Application Specific Integrated Circuit (ASIC) [3]. MEMS sensor is a vibratory response system of two fixed electrodes and one removable mass block [4,5], and it is a capacitive micro-accelerometer inertial sensor, its merits are that it can measure a constant accelerometer and balance the accelerometer according to the own electrostatic force and elastica [6], and then a constant voltage which is produced by the accelerometer of the earth shakes is exported. The capacitive micro-accelerometer sensor has the abilities of high sensitivity and accuracy, good stability, small temperature drifting and power consuming [7]; it can bring about closed loop feedback using electrostatic force.

MEMS sensor’s simplify internal structure is shown in fig.1. It can be seen from fig.1 that the main components of MEMS sensor are the end cap, the frame, the spring and the mass block. And it can be equivalent as a single freedom viscous damping second order vibratory system of a mass block and a spring [8].

Figure 1. The internal structure of MEMS sensor

B. Working principle of MEMS digital geophone Fig.2 is the sketch picture of the accelerometer sensor

two orders damping vibratory model. It uses the system’s linear performance to measure accelerometer, and Newton second law is applicative in this system.

Figure 2. The model of accelerometer sensor two order damping vibratory

The mass’ equation of forces is as follow:

makxdtdxc

tdxdm 2

2

(1)

Which, is the damping coefficient, k is the coefficient of elasticity,

cx is the displacement of the mass

and is the accelerometer. aLap lace-transform is performed on (1), the result is

shown as follow:

2010 International Conference on Artificial Intelligence and Computational Intelligence

978-0-7695-4225-6/10 $26.00 © 2010 IEEE

DOI 10.1109/AICI.2010.324

414

2010 International Conference on Artificial Intelligence and Computational Intelligence

978-0-7695-4225-6/10 $26.00 © 2010 IEEE

DOI 10.1109/AICI.2010.324

414

22

22

2

21

)(

1)()()(

rr

rr

ss

Qss

kcsmsm

sasxsH

(2)

Which,mk

r is the natural frequency of the mass,

cm

ckmQ r is the quality factor,

Q21

is the

damping factor. Equation (2) can be transformed when r , the

result is shown as follow,

21

)()()(

rxasxsH (3)

It can be seen from (3) that it is approximate linear relationship between the displacement and the accelerometer,

when r , the mechanical sensitivity ax

varies

inversely with the square of natural frequency , so it can

drop the natural frequency

2r

r to improve the sensitivity ax

of MEMS accelerometer sensor, and the natural frequency

r can’t be dropped too low because it is restricted by the mechanical structure and the manufacturing conditions.

Equation (3) can be transformed to (4) due to

mk

r , which is shown as follow:

mxasxsH

r

k1)()()( 2 (4)

It can be concluded from (4) that the natural frequency

r can be increased by increasing the coefficient of elasticity and decreasing the mass of the inertial mass. It provides the useful references for modulating the parameters.

III. EXPERIMENT AND DISCUSSION

The transition function has been discussed above, and then MEMS sensor is simulated. The simple diagram of the transition system is shown as follow:Finally, complete content and organizational editing before formatting. Please take note of the following items when proofreading spelling and grammar:

22 21H(s)

rrssFigure 3. The simple diagram of MEMS sensor transition system

A. Displacement response of the sinusoidal signal

In this experiment, the natural frequency r of the accelerometer sensor is 30 HzK , so the r 1.884 96 105 . The input accelerometer’s amplitude is

(20 ), and four accelerometers of different frequency are employed in the experiment, they are respective 10

srad / g22/ sm

HzK , 20 HzK ,50 HzK and 80 HzK . The output of the displacement response is shown as follow:

Figure 4. The displacement response of four different frequencies sinusoidal signal

It can be seen from fig.4 that the lower the accelerometer’s frequency is, the larger the amplitude of the displacement response is, while the accelerometer’s frequency is lower than the natural frequency. The larger the accelerometer frequency is, the larger the amplitude of the displacement response is, while the accelerometer frequency is larger than the natural frequency. So it can be analyzed that the sensor’s natural frequency should larger than the test accelerometer’s frequency to get better mechanical sensitivity in the case of the displacement is less small than the space between the polar.

B. Displacement response of the step signal The purpose of the experiment is to research relationship

between the damping factor and the system stability. The input signal is the step signal, and its amplitude is

(20 ). The natural frequency of the accelerometer sensor is also 30

g2 2/ smHzK .The seven different

damping factors are employed, and they are respective 0.2, 0.5, 0.707, 1, 2, 5 and 10, the displacement response is shown in fig.5:

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(a) The displacement response of 1

(b) The displacement response of 1

Figure 5. The displacement response of different damping factor

As shown in fig.5 (a), the system presents the oscillatory occurrence when the damping factor 1 , and the oscillation’s peak is higher the longer time is needed to get to the stable status when the damping factor is much smaller than 1. When the .20 , the system doesn’t achieve the stable status in 0.4 . ms

As it well shown in fig.5 (b), the system doesn’t present the oscillatory occurrence when the damping factor 1 , and longer time is needed to get to the stable status with the damping factor larger. When 10 , the system cost the most time to achieve the stable status.

In sum, the damping factor is the important factor in the accelerometer sensor’s design. When the damping factor 1, the time which the stable status needs is the shortest.

C. The close circuit system of MEMS digital geophone The diagram of the close circuit system is shown as

follow:

Figure 6. The close circuit system of MEMS digital

According to the seismic signal’s characteristic, the close circuit system’s measuring range is designed from -3g to +3g, the sensitivity is 30 , the natural frequency is 1 mV/g

HzK , the damping factor is 0.6 based on the above experiment, and the lowpass cutoff frequency is 300 Hz . The seismic signal is shown in fig.7, and it is generated by the finite-difference method of the seismic forward modeling, it is the only one trace in the data, and the sampling time is 0.004 and the sample number is 451. s

The output voltage of the close system is shown in fig.8. It can be seen from the fig.8 that the output voltage of the close system could sense well the seismic accelerometer, the approximate and the detailed are marching well.

Figure 7. The seismic signal

Figure 8. The output voltage of the close system

Figure 9. The comparison of the accelerometer and the output voltage

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Fig.9 shows the comparison of the input accelerometer and the output voltage, in which the full line is the seismic accelerometer and the dotted line is the output voltage. It can be seen that the output voltage has a delay to the seismic accelerometer and the overall trend is coincident

IV. CONCLUSIONS

According to the experiments, the design of MEMS digital geophone is feasible, and according to the mathematical model to design the parameters of the hardware and the results of the experiments show reasonable. The design plays the guidance role in the practical design of MEMS digital geophone.

REFERENCES

[1] Jingxing Dong. Micro inertial instrument – micro mechanical accelerometer. Beijing: Tsinghua University, 2003.

[2] Zhiping Xie. Sensor and measurement technology. Beijing: Electronic Industry Press, 2004.

[3] Li Zhang, Wenrong Xie. A brief introduction to acceleration triaxial digital geophone based on microelectronic mechanical system (MEMS). Coal Geology of China, 2006, 18(2):57-59.

[4] Maxwell P, Tessman J, Reichert B. Design through to production of a MEMS digital accelerometer for seismic acquisition. First Break. 2001, 19(3):141-143.

[5] Mougenot D. How digital sensors compare to geophone. Expanded Abstracts of 74th Annual Internet. SEG Mtg, USA, 2004:5-8.

[6] Jianfeng Li, Wei Huang, Zhongping Hu, Guoqing Ma. Development of MEMS-based digital geophone and analysis of its performance. Geophysical Prospecting For Petrole, 2005, 44(5):439-453..

[7] Zexi Han, Biao Li, Yuan Shao, Zhenghong Guo. Research on the development of seismic geophones. Petroleum Instruments, 2006, 20(6): 1-4.

[8] C Song, B Ha, S Lee. Micromachined inertial sensors. Proceedings of the 1999 IEEE/RSI international conference on intelligent robots and system, Korea Suwon. 1999:1049-1056.

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