地震信号检测

Detection of seismic signal using fiber Bragg grating sensors Yan Zhang, Sanguo Li, Robert Pastore, Zhifan Yin, Hong-liang Cui
Department of Physics and Engineering Physics, Stevens Institute of Technology,
Hoboken, NJ, USA 07030
ABSTRACT
An unattended seismic sensor based on optical fiber Bragg grating (FBG) sensing technology is presented in this paper. One of the applications is its deployment in the battlefield remote monitoring system to detect the presence of personnel, wheeled vehicles, and tracked vehicles. The customized FBG sensor prototype is demonstrated which consists of two FBG sensor/demodulation grating pair attached on a spring-mass mechanical system. The sensor performance is evaluated in laboratory and the field tests were carried out in the shooting range using the conventional military Rembass-ⅡS/A sensor (remotely monitored battlefield sensor system Ⅱseismic acoustic sensor) as the benchmark. Personnel and a series of vehicles were used as targets. The experimental data of the field test show that the FBG sensor averaged a 30.20 % greater detection range than the Rembass-ⅡS/A sensor. It is hoped that the FBG sensor system will be a promising tool for real time monitoring system in the battlefield applications.
KEYWORDS Fiber Bragg grating sensor, Seismic signal detection
1. INTRODUCTION
Unattended ground sensors have been widely deployed in the battlefield remote monitoring system to detect, classify, and determine direction of movement of personnel, wheeled vehicles, and tracked vehicles. The categories include miniature acoustic, seismic, chemical, magnetic, visual, and IT imaging sensor systems.
In recent field trials, seismic sensors have shown their applicability to target bearing, range, and classification problems in battlefield monitoring and perimeter intruder detection systems [1]-[5]. The FBG based seismic sensor, especially, can perform accurate measurements of small ground vibration and monitor seismic activity due to its high sensitivity to dynamic strains induced by acceleration variations [6]-[8].
In this paper we will present our customized FBG seismic sensor. The detection is implemented by the FBG dynamic strain sensor attached on a spring-mass system. The acceleration of ground motion is transformed into the strain signal of the FBG sensor through this mechanical design, and after the optical demodulation generates the analog voltage output proportional to the strain changes.
This FBG sensor has the advantages of low power consumption and light weight. It is also passive, which can be easily hidden without any radio frequency emission or thermal signature to the environment. Furthermore, fiber Bragg gratings are appropriate for multiple-sensor networks as many of these gratings can be deployed either in series or in parallel.
2. SENSOR DESIGN AND LABORATORY TEST
2.1Sensor head mechanical design
The basic detection principle of the seismic sensor is that when the movement of intrusion (personnel and vehicles) initiate near the ground surface, the seismic waves will propagate and spread out along spherical wave fronts in all directions. Some of the waves go along the ground surface as direct stress waves. Others will travel through the earth.
Photonic Sensing Technologies, edited by Michael A. Marcus, Brian Culshaw, John P. Dakin,
Proc. of SPIE Vol. 6371, 63710R, (2006) · 0277-786X/06/$15 · doi: 10.1117/12.686166
When they encounter the interface of two layers with different physical properties, part of them will reflect back toward the surface. Waves from all directions together with ground rolls along the surface can contribute to the acceleration change of the sensor enclosure.
Fig. 1. FBG seismic sensor head design
The design of FBG seismic sensor head is shown in Fig. 1. The two ends of the fiber Bragg grating sensor are fixed directly on the leaf spring of a spring-mass configuration. The leaf spring is used here to minimize cross-axis sensitivity. In this design, the Bragg grating is uniformly tensioned to get a constant strain distribution over it. By employing this configuration, the Bragg grating is always have a sharp reflection characteristic with no broadening in its reflection spectrum during the wavelength shifting. The inert mass (material: brass, weight: 10.6 grams) is attached to one end of the leaf spring (material: stainless steel, length: 4 cm, width: 1.2 cm, thickness: 0.2 cm). The other end of leaf spring is supported by a supporting pole (height: 1.27 cm). This pole is fixed on the base of sensor enclosure and the whole sensor head is fully coupled into the earth during the field test with only the optical cable stretching out.
The movement of personnel and vehicles induces ground vibrations, with attendant weak seismic waves emanating from the location of such activity. Seismic waves introduce the acceleration change on the sensor enclosure together with the supporting pole at one end of the leaf spring. While the inert mass hanging at the other end of the leaf spring remains static, it induces the strain variation on the leaf spring together with the FBG sensor. The strain change of the fiber Bragg grating can be detected by the Bragg wavelength shift according to the sensing principle.
The mechanical system of the sensor head can be modeled as a single-degree-of-freedom system. The leaf spring and the fiber grating can be simplified as the springs with stiffness K1 and K2. The natural frequency of the system increases with increase of K1, a, K2 and decrease of b, M. By adjusting the parameter of a, b, M and choosing material K1, the system is customized as the low frequency response sensor. In the personnel and vehicle seismic detection application, the interested frequency bandwidth is usually 10-200 Hz. The resonant frequency of the cantilever is designed to be 30-40 Hz as a sensor responding to the low frequency. There is also no damping technique applied on the spring-mass system in the field test.
2.2Interrogation scheme
The FBG sensor interrogation scheme is illustrated in Fig. 2. The system consists of the broadband light source, FBG ground sensor coupled with spring / mass configuration, demodulator FBG grating, optical circulator, 3-dB optical couplers, signal detection and processing hardware.
Fig. 2. Interrogation scheme of FBG sensor detection system
Light from a broadband source (central wavelength at 1550nm and a spectral width of 40 nm, optical power 54 mW) is launched into a single mode fiber, and then enters one of the ports of the optical circulator. The light goes to the sensor grating and is reflected from the sensor grating back into one port of the 3dB coupler, then enters into the demodulator grating.
The reflected light of the demodulator grating exits from the 3dB coupler, and then goes into the photodetector (responsivity: 0.65A/W, JDS Uniphase, ETX 100), where the optical signal is converted into analog electrical signal. The output analog electrical signal from the photodetector goes through a custom-designed electronic band-pass filter and amplifier. The processed signal is collected by a PC running LabVIEW, which has a sampling rate of 2 MHz per channel for eight analog input channels.
Both of the gratings have the same parameter (central wavelength: 1550nm, bandwidth: 0.4 nm, reflectivity: 99%, length: 1 cm) under static conditions. The first sensor grating is installed on a spring-mass system and has a wavelength shift under strain. It functions as an optical reflector while the other demodulator grating is a reflecting intensity modulator with no tension on it. By this way, the output light intensity is directly related to the amount of dynamic strain variation on the sensor grating.
In addition to the strain signal, the fiber grating is also a sensitive element to the environmental temperature variation. To separate this influence with the strain signal sensing, temperature compensation is implemented by integrating the sensor grating and demodulator grating in close proximity to one another [9]. The FBG sensor is coupled with the inert mass where the acceleration is to be measured. The demodulator grating is not subject to strain and measures the temperature only. The grating pair also has the same temperature factor to ensure that during the homogenous temperature change both gratings shift the central wavelength in the same way, so that the peak position of the sensor grating is always self-referenced to the temperature-sensitive demodulator grating.
While my customized sensor design measures the dynamic strain signal in ac form between 10-200 Hz, the environmental temperature variation which usually exists as a near dc signal will not introduce noise and affect the detection sensitivity after passing through the band-pass filter. However, the severe uneven temperature distribution inside the sensor head might influence the dynamic gain and the detection linearity of the system based on the lateral filtering principle.
When an intruder or a vehicle is attempting to approach the destination, the signal data is captured by the sensor head on-site and then transmitted back to the data acquisition system at certain distance away. The transmission line between the sensor head and the signal acquisition and processing part is commercial outdoor optical cable directly buried in the ground which has no electromagnetic radiation to the environment. The information is processed and recorded in real time by the data acquisition system. By this means, the whole detection system operates in remote sensing remote control mode to guarantee the operation safety and convenience in the battle action.
2.3 Laboratory test result
A serial of experiments are conducted in the laboratory to test the performance of the FBG sensor.
Fig. 3. FBG sensor performance test on the vibration stage
As shown in Fig 3, the FBG sensor is mounted on a vibrator in order to apply known levels of acceleration. We drive the vibrator using a sinusoidal wave and obtain the peak-to-peak value of the output voltage of the FBG sensor. The result shows that the FBG sensor responds linearly to the external vibration signal. The correlation coefficient of the linear fit data is calculated to be 0.99533. The minimum strain resolution of the FBG sensor is 1 µε and a short-term stability ~2.5 µε.
The sensor detection dynamic range is estimated at the frequency of 30 Hz. With the maximum output value at 6 V and background noise at 0.6 mV rms (electronic amplified at 3×103), we can get the result that the system dynamic range
of FBG sensor at 30 Hz is 80 dB.
Conventional moving-coil geophone
FBG sensor
We did the temperature cycle test by putting the FBG sensor into a digital controlled oven ranging from room temperature (27 ℃) to 56 ℃. Analysis of the spectrum of the grating pair shows that the peak position of the sensor grating is always self-referenced to the demodulator grating within this temperature range.
One of the significant advantages of the FBG sensor is immunity to the electromagnetic interference. To verify this advantage, we put the 60 Hz AC current power supply near the FBG sensor and observe the sensor response. A conventional moving-coil geophone shown in Fig 3 is used for comparison. This kind of conventional geophone detect the seismic signal when the particle motion in the earth moves the geophone body, which houses a magnet within a suspended coil inside the geophone. This action produces an analog voltage signal that is proportional to the ground motion.
Fig 4 is the response of both sensors in time domain. Here the x-axis is the time domain in unit of ms and the y axis the output voltage of both sensors. The conventional moving-coil geophone has signal response to the power supply in a sine wave while the FBG sensor shows only background noise in the figure. The Fourier frequency analysis of the signals shows that the conventional geophone has peak signal in 60 Hz while FBG sensor has no significant frequency peak and is absolutely immune to the EMI.
Fig 4. Time domain of FBG sensor response to 60 Hz AC current
(upper: FBG sensor, lower: conventional moving-coil geophone, x: time y: output voltage)
3. FIELD TEST RESULT
3.1First field test result
The first field test of intrusion detection was carried out at the shooting range of Fort Dix. Target source included personnel (weight: 55-95 Kg), a military High Mobility Multi-Purpose Wheeled Vehicle – HMMWV (weight: 2655 Kg, speed 32 Km/h), and a military wheeled truck (weight: 6089 Kg, speed 32 Km/h). The distances were measured and calibrated by a military GPS system (Model: Garmin etrex, accuracy: ±5m). The presence of the object can be captured using the first impulse of the signal to trigger at a certain level. The detection distance is interpreted as the maximum distance where the seismic signal can trigger and get recorded by the detection system. The field test results are listed in Table 1.
Table 1 FBG sensor detection capability in first field test
In the field test no damping technique was incorporated in the sensor head. The result shows that the sensor has a higher sensitivity to the impulse-like signal such as jumping. This is because the pulse signal is a combination of many different frequencies that may contain the resonant frequency of the spring-mass system, while the frequency of the man-running signal is relatively monochromatic which may not be near the maximum frequency response of the spring-mass system. The sensor head can only give a high response in the narrow band signal frequency without gain flattening.
3.2Second field test result
The second field test was carried out at Eglin Air Force Base. The main purpose of this test is to determine the sensitivity of the FBG sensor compared with the existing Army seismic sensors. The Rembass-ⅡS/A sensor (remotely monitored battlefield sensor system Ⅱseismic acoustic sensor) is used as the benchmark. This commercial military sensor responds to seismic (ground vibration) and acoustic (sound) activity within detection zone radius and the sensor provides the functions of detection, location and classification.
Two kinds of sensors were placed in the same location along a dirt road. The terrain consisted of flat sandy desert-like soil. There were no trees or other objects between the sensors and targets. The area was also fairly remote without noise or movement near by. The temperature ranged from 15 ℃ to 17 ℃and wind speed averaged 1.53 to 2.04 m/s.
The detection results of both FBG sensor and military REMBASS-Ⅱseismic sensor are listed for comparison in Fig 5. The detection targets category along x-axis includes two people and a series of seven military vehicles. The detection distance can be interpreted as the maximum distance which sensor can respond to the target. The actual detection distance in each category is the average result of several tests repeated under the same condition. Again, no damping is
used in the test because we only use the first impulse of the seismic signal as the trigger signal to decide the maximum detection range. The distance-to-target was calculated based on each vehicles on-board GPS receiver which recorded time and position in 1 second intervals. The comparison figure shows that the FBG sensor equaled or outperformed the REMBASS-Ⅱsystem with both personnel and every wheeled vehicle except category 9, where the results were very close.
D e t e c t i o n d i s t a n c e ( u n i t : k m )
D e t e c t i o n t a r g e t s c a t e g o r y
Fig 5. FBG sensor detection capability comparisons to REMBASS-Ⅱ sensor
4. CONCLUSION AND DISCUSSION
The feasibility of an unattended FBG seismic sensor is demonstrated. The comparison of its sensitivity–distance to target with the existing Army seismic sensor shows that the FBG sensor averaged a 30.20 % greater detection range than the REMBASS-Ⅱsystem.
More engineering measures of sealing and packaging of the cables and sensors are undertaken to ensure that the sensor can be deployed below grounds for extended periods especially in the harsh military environment. The expected error signals which may affect the sensor performance include: seismic signals generated by different motors working in vehicles without moving, different natural obstructions (trees, stones, and moving rivers) between target and sensor, etc. More systematic research will be focused on this area. Having the potential capability of detecting time critical targets (personnel and vehicles), the FBG sensor system will be a promising tool for real time situational awareness system in the battlefield applications.
ACKNOWLEDGMENTS
The authors would like to gratefully acknowledge the support of Dr. Kurt O'Donnell, Mr. Michael Pellicano and Mr. Richard Luttrell in U.S. Army CERDEC, Fort Monmouth, NJ for their cooperation in carrying out the field test successfully.
REFERENCES
1.John P. F. Wooler, Roger I. Crickmore, “ Fibre optic sensors for seismic intruder detection”, 17th International
Conference on Optical Fiber Sensors, pp. 278-281, 2005
2.Michael S. Richman, “Personnel tracking using seismic sensors”, Proceedings of SPIE Vol. 4393, pp. 14-21, 2001
3.Juan C.Juarez, “Polarization discrimination in a phase-sensitive optical time-domain reflectometer intrusion-sensor
system”, OPTICS LETTERS, Vol.30, No.24, pp.3284-3286, 2005
4.Juan C.Juarez, “Distributed Fiber-Optic Intrusion Sensor System”, JOURNAL OF LIGHTWAVE
TECHNOLOGY, Vol.23, No.5, pp.2081-2086, 2005
5.Jinhui Lan, Tian Lan, and Saeid Nahavandi, “A Novel Application of a Microaccelerometer for Target
Classification”, IEEE SENSORS JOURNAL, VOL. 4, NO. 4, pp 519-523,2004
6.M. Willsch, etc “Highly sensitive micro mechanical fiber Bragg grating acceleration sensor combined with a new
interrogation principle”, Proceedings of SPIE Vol.4074, P46-53, 2000
7. A. Mita, I. Yokoi, “Fiber Bragg grating accelerometer for buildings and civil infrastructures”, Proceedings of SPIE,
vol. 4330, pp. 479-486, 2001
8.S.J. Spammer, P. L. Fuhr “Temperature insensitive fiber optic accelerometer using a chirped Bragg grating”, Opt.
Eng. Vol.39(8), pp. 2177-2181, 2000
9.W.L. Schulz, E. Udd, J.M. Seim, H.M. Laylor, G.E. McGill, “Single and multiaxis fiber grating based strain
sensors for civil structure applications”,Proceedings of SPIE, Vol. 3489, ,pp. 71-80, 1998。