chung-ray chu ching-jer huang tsung-mo tien department of hydraulic and ocean engineering national...

Chung-Ray Chu Ching-Jer Huang Tsung-Mo Tien

Department of Hydraulic and Ocean EngineeringNational Cheng Kung University

Taiwan.

April 20, 2023

A novel fiber optic sensing system for monitoring debris flows

The Second World Landslide ForumRome, Italy

The Second World Landslide ForumThe Second World Landslide Forum Rome, ItalyRome, Italy

• Introduction• Fiber-optic sensor• Fiber-optic sensing system for debris flow• Calibration experiment• Conclusion

Outline

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Introduction

• Debris flow is one of the most hazardous nature process in Taiwan.• Debris flow has the following characteristics (Takahashi, 1991):

– The forefront looks like a bore and accumulates the largest rocks. – The flow following the forefront appears as a mudflow with a gradually decreasing discharge.– The flow is accompanied by loud noise and ground vibration.

• The debris flow warning systems can be divided into two categories (Arattano and Marchi 2008):

– Advance warning system (e.g. rainfall).– Event warning system (e.g. ground vibration sensing), with short evacuating time but precise

alarm.

• Conventionally, geophones or seismometers are often utilized to detect the ground vibrations produced by debris flows. However, the electrical power supply and signal attenuation are the challenges in remote mountainous region.

• The technique of fiber optic sensing is appropriate for remote sensing purpose, because of its very low optical loss, high sensitivity, and immunity to electromagnetic interference.

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Fiber-optic sensor

• The advantages of fiber-optic sensor– Low optical loss– Multiplexibility– High sensitivity– Immunity to electromagnetic interference

• Sense various physical signals– Strain– Temperature– Pressure– Acceleration

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• The shift of Bragg wavelength due to strain and temperature changes is given by (Kersey et al. 1977)

• In respect to measurand of ground vibrations, thermal effects are relative to very-low frequency component and could be igmored.

Fiber-optic sensor• Fiber Bragg Grating (FBG) sensor• Photosensitive effect (Hill et al. 1978):

intense UV light can cause permanent change in refractive index of optic fiber.

• Broadband light incident in the grating, and a narrowband component reflected back. (Kersey 1977)

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B 2n

2

12 11 122 12

dndT

B

nn P P P T

n

Be

B

P

Figure 1 Basic Bragg grating-sensing mechanismFigure 1 Basic Bragg grating-sensing mechanism


Fiber-optic sensor• FBG accelerometer acting with a external force

• Strain:

• Hook’s law:

• The relationship of resonance wavelength and acceleration:

• Multiplexing: • Multiplexing allows each sensor to be assigned

to a different wavelength in the available source spectrum.

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Figure 3 FBG sensor serial multiplexingFigure 3 FBG sensor serial multiplexing

Figure 2 Diagram of simple FBG accelerometer design.Figure 2 Diagram of simple FBG accelerometer design.

1 B

e B

L

L P

ML a

K

EAK

L

eB

B

PMa

EA

B 2i in


Fiber-optic sensing system for debris flow

Name of creek Sensor 1 Sensor 2 Sensor 3 Sensor 4

Ai-Yu-Zi 625 m 520 m 340 m 144 mChu-Shui 595 m 368 m 195 m 50 m

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Figure 4 Topographic map of the fiber optical sensing systems deployment.Figure 4 Topographic map of the fiber optical sensing systems deployment.

Table 1 Distances between the sensors and the data receiving center.Table 1 Distances between the sensors and the data receiving center.

• Fiber optics sensing system deployed in the middle of Taiwan.

• Line array construction– advance detection– spatial analysis of the moving process

• Decay rate of optical signal– 0.383 dB/km

• Sensor: single-axis accelerometer, GS-6500 (FiberSensing company)

– sensitivity: 10 pm/g– frequency response: < 300 Hz– amplitude range: ± 40 g– accuracy: 20 mg


Calibration experiment

(a)

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0 1 2 3 4 5 6 7 8

x 104

-0.4

-0.2

0

0.2

0.4

Time (ms)

acc

ele

ratio

n (

m/s

2)

CH1 27-Aug-2010 09:53:24

0 50 100 150 200 2500

0.0005

0.001

0.0015

0.002

Frequency (Hz)

Sp

ect

rum

CH1 27-Aug-2010 09:53:24

(c)

(c)

Figure 5: Testing signal measured by AYZ-4 sensor; (a) time domain, (b) frequency domain, and (c) time-frequency domain by Gabor transformation.

Figure 5: Testing signal measured by AYZ-4 sensor; (a) time domain, (b) frequency domain, and (c) time-frequency domain by Gabor transformation.

• The first test



(a)

99

(b)

(c)

Figure 8 Vertical ground vibration measured by the Z-axis component of geophone versus vertical acceleration of ground vibration measured by the FBG accelerometer. The signals were recorded for 30 s, and well aligned to the first impact pulse. (a) Vertical velocity of ground vibration in time domain, and (b) in frequency domain. (c) Vertical acceleration of ground vibration in time domain, and (d) in frequency domain.

Figure 8 Vertical ground vibration measured by the Z-axis component of geophone versus vertical acceleration of ground vibration measured by the FBG accelerometer. The signals were recorded for 30 s, and well aligned to the first impact pulse. (a) Vertical velocity of ground vibration in time domain, and (b) in frequency domain. (c) Vertical acceleration of ground vibration in time domain, and (d) in frequency domain.

0 5000 10000 15000 20000 25000 30000-8

-6

-4

-2

0

2

4

6

8

Time (ms)

Vel

ocity

(cm

/s)

0 50 100 150 200 2500

0.0005

0.001

0.0015

Frequency (Hz)

PS

D (

(cm

/s)2 /H

z)

0 5000 10000 15000 20000 25000 30000-4

-3

-2

-1

0

1

2

3

4

Time (ms)A

ccel

erat

ion

(m/s

2 )0 50 100 150 200 250

0

0.0001

0.0002

0.0003

0.0004

0.0005

Frequency (Hz)

PS

D (

(m/s

2 )2 /Hz)

(d)

Figure 6 Sketch of calibration experiment setup.

Figure 6 Sketch of calibration experiment setup.

Figure 7 Picture of experimental site.Figure 7 Picture of experimental site.



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Figure 9: Signal-to-noise ratio (SNR) calculated through the time axis. SNR from Z-axis of geophone (solid line), FBG accelerometer (dotted line), and microphone (dashed line).

Figure 9: Signal-to-noise ratio (SNR) calculated through the time axis. SNR from Z-axis of geophone (solid line), FBG accelerometer (dotted line), and microphone (dashed line).

0 5 10 15 20 25 30-10

-5

0

5

10

15

20

25

30

35

Time (s)

S/N

(dB

)

Z-axis

MicrophoneFBG

• Signal-to-noise ratio (SNR) (Itakura et. al. 2000)

E

mean

SNR 10logS

N

2

E 0

2mean 0

1

1

T

M T

jj

S S t dt T

N N t dt TM


Conclusion

• This study presents a novel fiber optic sensing system for monitoring debris flows. Two sensing systems were deployed along the Ai-Yu-Zi Creek and the Chu-Shui Creek in Nantou County, Taiwan with Fiber Bragg Grating (FBG) accelerometers for monitoring debris flows. In each system four accelerometers were installed in the bank of the creek as line arrays.

• A calibration experiment was carried out to compare the performance of FBG accelerometer with other sensors, such as geophone and microphone. The result showed that the SNR of FBG accelerometer was higher than geophone; moreover, was much higher than microphone. The different performance was born of the sensitivities of the used sensors, and the material where the signals propagated.

• Even though the sensing capability of FBG accelerometer seems better than geophone, the temperature effect and other ambient noise should be considered. Low frequency contribution would be involved from the temperature changes. Ambient noises would be sensed from traffic, water flow, or other tremors. These effects will cause the false alarm of detecting and warning system.

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Reference

• Arattano M, (2003) Monitoring the presence of the debris-flow front and its velocity through ground vibration detectors. In: Debris-Flow Hazards Mitigation: Mechanics, Prediction, and Assessment, Proceedings of the Third International Conference on Debris-Flow Hazards Mitigation, Davos, Switzerland, Rotterdam, Netherlands, September 10–12 2003. Millpress, pp 719-730

• Arattano M, Marchi L, (2008) Systems and sensors for debris-flow monitoring and warning. Sensors 8 (4):2436-2452• Berti M, Genevois R, LaHusen R, Simoni A, Tecca PR, (2000) Debris flow monitoring in the Acquabona watershed on the

Dolomites (Italian Alps). Physics and Chemistry of the Earth Part B-Hydrology Oceans and Atmosphere 25 (9):707-715• Burtin A, Bollinger L, Cattin R, Vergne J, Nabelek JL, (2009) Spatiotemporal sequence of Himalayan debris flow from

analysis of high-frequency seismic noise. Journal of Geophysical Research-Earth Surface 114. doi:F04009 10.1029/2008jf001198

• Hill KO, Fujii Y, Johnson DC, Kawasaki BS, (1978) Photosensitivity in Optical Fiber Waveguides - Application to Reflection Filter Fabrication. Appl Phys Lett 32 (10):647-649

• Huang C-J, Yin H-Y, Chen C-Y, Yeh C-H, Wang C-L, (2007) Ground vibrations produced by rock motions and debris flows. J Geophys Res 112:F02014

• Itakura Y, Fujii N, Sawada T, (2000) Basic characteristics of ground vibration sensors for the detection of debris flow. Phys Chem Earth (B) 25 (9):717-720

• Itakura Y, Inaba H, Sawada T, (2005) A debris-flow monitoring devices and methods bibliography. Natural Hazards and Earth System Sciences 5 (6):971-977

• Itakura Y, Koga Y, Takahama JI, Nowa Y, (1997) Acoustic detection sensor for debris flow, in Debris-Flow Hazards Mitigation: Mechanics, Prediction, and Assessment. In: Proceedings of the First International Conference, N. Y., 1997. Am. Soc. of Civ. Eng., pp 747-756

• Iverson RM, Reid ME, LaHusen RG, (1997) Debris-flow mobilization from landslides. Annual Review of Earth and Planetary Sciences 25:85-138

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Reference

• Johnson AM, Rodine JR, (1984) Debris flows. In: Brunsden D, Prior DB (eds) Slope Instability. John Wiley & Sons. Ltd., pp 257-361

• Kersey AD, (1997) Multiplexing Techniques for Fiber-Optic Sensors. In: Dakin J, Culshaw B (eds) Optical Fiber Sensors: Applications, Analysis, and Future Trends, vol IV. pp 369-407

• Kersey AD, Davis MA, Patrick HJ, LeBlanc M, Koo KP, Askins CG, Putnam MA, Friebele EJ, (1997) Fiber grating sensors. J Lightwave Technol 15 (8):1442-1463

• Lavigne F, Thouret JC, Voight B, Young K, LaHusen R, Marso J, Suwa H, Sumaryono A, Sayudi DS, Dejean M, (2000) Instrumental lahar monitoring at Merapi Volcano, Central Java, Indonesia. Journal of Volcanology and Geothermal Research 100 (1-4):457-478

• Lin CH, Kumagai H, Ando M, Shin TC, (2010) Detection of landslides and submarine slumps using broadband seismic networks. Geophysical Research Letters 37. doi:10.1029/2010GL044685

• Massimo A, (2000) On debris flow front evolution along a rorrent. Phys Chem Earth (B) 25 (9):733-740• Okuda S, Okunishi K, Suwa H, (1980) Observation of debris flow at Kamikamihori Valley of Mt. Yakedade. In: the 3rd

meeting of IGU commission on field experiment in geomorphology, Disaster Prev. Res. Inst. Kyoto Univ., Japan, 1980. pp 127-130

• Takahashi T, (1991) Debris Flow. A A Balkema,

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Thank you for your attention

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chung-ray chu ching-jer huang tsung-mo tien department of hydraulic and ocean engineering national...

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