Abstract

In this work we demonstrate a low-frequency acoustic sensor structure based on extrinsic Fabry-Pérot interferometer (EFPI) cavity. The cavity is fabricated through micromachining techniques in a square silicon substrate with 4 mm side length and 400 μm thickness, which gives the sensor relative compact size. In the assembling process of the lead-in fiber, a D-shaped ceramic ferrule is designed to achieve the open cavity structure, which can balance the environmental pressure inside and outside the cavity and thus giving the sensor potentials of resisting strong pressure variations in some harsh application environments. Experimentally, sensor response to low-frequency acoustic waves from 0.1 Hz to 250 Hz is measured and demonstrated. A flat response region between 0.5 Hz to 250 Hz with sensitivity fluctuation of 0.8 dB is realized. Pressure resistant test of 25 MPa is also conducted on the sensor and exhibited to prove the function of the open cavity structure.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. Introduction

Low-frequency acoustic waves or even infrasound signals exist uniquely in many situations due to characteristics of low attenuation, strong diffraction capability, and long propagation distance. Therefore, detection of low-frequency acoustic waves can be an effective method in early-warning and monitoring of some natural disasters or artificial accidents such as debris flow [1], volcano eruption [2], earthquake [3], tornado [4], and pipeline leakage [5], etc. Traditional methods for acoustic detection are commonly based on piezoelectric materials [6,7], which can generate voltage output when responding to acoustic pressure. This kind of techniques often require complex electronic components or circuits for the signal readout and processing, thus resulting in limitations for application in harsh environments.

Due to the inherent superiority of compact size, light weight, corrosion resistance, remote operation capability and immunity to electro-magnetic interference (EMI), optical fiber-based devices have become an outstanding alternative for acoustic wave detection and have attracted great research interests, such as fiber interferometers [8–18], fiber gratings [19–22], specialty fibers [23,24], and fiber laser [25–28], etc. Among different optical acoustic sensor structures, diaphragm based Fabry-Pérot (FP) cavity is a significant candidate structure for acoustic wave or even infrasound sensing [11–18] due to its unique characteristics of reflection-based working principle, which allows it to be easily packaged as sensing probes. FP cavities for acoustic sensing are usually formed between two optical reflection facets, one is a fixed reflector, while the other is a diaphragm that can vibrate under sound exposure. For many reported FP acoustic sensors, diaphragms are usually glued and assembled to the sensor structures by manual operations [11–14], thus the precise parameters (diaphragm form factor, internal force) control and uniformity among different sensors of a same structure could be a vital limit. Besides, the manually gluing process of the diaphragm also makes it challenging to obtain a relative compact size for the FP cavity, thus leading to a lower resonant frequency and degrade the response flatness within the low-frequency range. For example, in [12] the FP sensor with a glued parylene-C diaphragm shows a resonant frequency at 13 Hz, and therefore the sensitivity fluctuation below 100 Hz is about 20 dB. Some EFPI sensor structures fabricated from micromachining techniques have also been reported [16–18]. Nevertheless, in these structures, only the diaphragm is fabricated by micromachining, which means that a transferring process is necessary to assemble the diaphragm to the fiber pigtail. For example, in [16] and [17], silver film is firstly sputtered on the photoresist on a silicon substrate, and a tube with epoxy attached is pushed to the film, and finally separated from the substrate by dissolving the photoresist in acetone. The transferring procedure might have the risk in affecting the diaphragm, such as internal stress disturbing. In addition, for FP sensors with closed cavity structure, diaphragm could be very sensitive to environmental pressure fluctuations and may even be damaged in some high-pressure situations such as hydrophone or downhole applications.

In this article, we demonstrate a micromachined extrinsic Fabry-Pérot interferometer (EFPI) cavity for low-frequency acoustic wave sensing. The FP cavity is fabricated in a silicon substrate, while the diaphragm that picks up the acoustic wave is a two-layer composite membrane (silicon nitride of 1 μm thickness and titanium of 500 nm thickness) that deposited on the substrate. The composite layer is designed to maintain a good reflectivity and interferential contrast if water flows into the cavity, which is experimentally verified, giving the sensor potentials to work in high-humidity situation or even liquid environment. The sensor fabrication method we proposed in this manuscript is free from diaphragm transferring procedure or other manual operations since the film and cavity structure are both fabricated on a same silicon wafer through micromachining techniques. Benefit from this, the risk of diaphragm damaging or internal stress perturbations can be decreased. Subsequently, the mechanical and optical properties of the film and cavity can be precisely controlled, and uniformity in sensor characterization can be also guaranteed. In our work, a compact cavity size (1 mm diameter) is easily achieved. In the assembling process of the lead-in fiber, we designed a D-shaped ceramic ferrule for installation since it will form an open cavity hole, which can balance the environmental pressure (gas or liquid) inside and outside the cavity and give the sensor potential to work under some high-pressure situations. In this work, we experimentally demonstrate the sensor response to low-frequency acoustic wave ranging from 0.1 to 250 Hz, and a flat response range between 0.5 to 250 Hz with phase sensitivity fluctuations of 0.8 dB is observed. The pressure resistant performance of the sensor is also proved by applying 25 MPa water pressure.

2. Sensor configuration and fabrication

The proposed EFPI cavity for low-frequency sensing is formed between two reflection facets. The first facet is the cleaved fiber end face. A silicon nitride diaphragm which functions as the sensing element to pick up acoustic signals will act as the second reflector at the same time. Silicon nitride is selected as the sensing material here due to its higher refractive index (RI) than silica, which is another common alternative in micromachining process. The higher RI value can enhance the Fresnel reflectivity. Besides, the larger Young’s modulus and Poisson’s ration values of silicon nitride can decrease the risk of diaphragm corrugation in the cavity fabrication. In our design, to extend the potential applications of our sensor to underwater situations, a layer of 50 nm-thick copper is coated on the cleaved fiber end to guarantee the reflectivity of the first reflector under water, since the refractive index of the fiber core (1.46) is close to that of water (1.33) and subsequently the reflected power will decrease sharply in water environment. The fiber end with 50 nm copper film can provide a reflectivity of about 9%. For the second reflection at the air-Si3N4 interface, the Fresnel reflectivity can be calculated to be about 11%. Due to the spatial loss in the cavity, this value can’t provide the second reflected beam with enough power to match with the first reflected beam to form a good contrast. Therefore, in our design an extra layer of titanium is deposited on the silicon nitride to enhance the second reflection ratio. Here we put forward some analysis about spatial loss in air cavity to explain this.

The transmission coefficient η and the corresponding loss α can be expressed by the following Eq. (1) [29]. In the equations, w1 and w2 are the field radius of the sending and receiving fibers. L is the cavity length, nair is the RI of the air (≈1), while k stands for the wavenumber. In the EFPI cavity sensor structure, the sending and receiving fiber is the same one, so we have w1 = w2 = w. The filed radius w can be given by an analytic approximation shown by Eq. (2) [29]. V is the fiber’s normalized frequency and a represents the core radius of the fiber. With the conditions above, the roundtrip transmission coefficient η in the cavity can be simplified as Eq. (3). The input fiber of the EFPI cavity is the standard SMF-28e single mode fiber. According to the known parameters, we can simulate the relationship between the transmission coefficient and loss in the cavity with the cavity length. The simulation result is exhibited by Fig. 1.

 

Fig. 1 Simulation of transmission coefficient (blue curve) and loss (red curve) with air cavity length.

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{η=4(4z2+w12w22)(4z2+w12+w22w22)+4z2w22w12z=2Lnairkw1w2α=1η
wa=0.65+1.619V3/2+2.879V6,V=2πaλncore2nclad2
η=11+(λL/πw2)2

From the simulation results in the above Fig. 1 we can see that when the cavity length is about 52 μm, the beam after a roundtrip traveling in the cavity will experience a loss of 3 dB. Under this cavity length, the EFPI interferential spectrum has a free spectral range (FSR) of about 23.1 nm. In our white light interferometry (WLI) phase demodulation which will be discussed in the next section, the optical bandwidth of the FBGA interrogator is about 40 nm (1525 nm to 1565 nm). If the FSR is too large (like 20 nm), the number of interferential cycles that can be sampled will be too small to distinguish the spatial frequency of the sensor for WLI phase calculation. Hence, our proposed sensor should have a cavity length of larger than 100 μm, where the transmission coefficient is less than 30% according to Fig. 1. It is obvious that the 11% Fresnel reflection at the Si3N4 interface can’t guarantee the fringe contrast. To solve this issue, we designed a composite diaphragm formed by one layer of silicon nitride and one layer of titanium. The fabrication process will be explained in the subsequent text.

The sensor fabrication process is described by Fig. 2, including wafer micromachining and sensor assembling. As shown in Fig. 2(a), a layer of silicon nitride (Si3N4) with 1 μm thickness is deposited on a 400 μm thick silicon substrate by low pressure chemical vapor deposition (LPCVD) technique. Then a layer of 500 nm thick titanium (Ti) film is deposited on the silicon nitride layer. The titanium layer is adopted here to guarantee the reflectivity and interferential fringe contrast, as discussed above. The composite diaphragm structure can also guarantee the reflectivity underwater with the assist of the copper coated on the cleaved fiber end. As the composite layer diaphragm is prepared, fabrication of the FP cavity will be the next step.

 

Fig. 2 Schematic diagram of sensor fabrication process including (a) wafer micromachining; (b) sensor assembling; (c) sensor real image.

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The design for the EFPI structure includes a circular groove with 2.5 mm diameter and FP cavity with 1 mm diameter. On one hand, the groove can immobilize the ceramic ferrule that delivers the lead-in fiber to the cavity and prevent it from touching and damaging the diaphragm. On the other hand, it can also be an effective tool for cavity length control with high precision and uniformity. To realize the designed structure, a first-step deep reactive ion etching (DRIE) with 2.5 mm window diameter and 350 μm depth is performed on the reverse side of the substrate to fabricate the groove. The groove diameter is selected to match the outer diameter of the ceramic sleeve that will be used in the sensor assembling. Then the second-step DRIE is conducted on the center of the groove with 1 mm window width (i.e. the cavity diameter) and 50 μm depth. That means, all the silicon is removed by the DRIE process within the 1 mm diameter window region at the central of the silicon substrate to form the air-cavity, and subsequently the composite Si3N4 and Ti layer in this region becomes a diaphragm, which plays the role of picking up acoustic signals and phase-modulating the reflected optical beam in the EFPI cavity.

After these technical steps, the micromachined cavity structure is completed. The sensor assembling process, that is, installing the lead-in fiber to the cavity, is demonstrated in Fig. 2(b). In this procedure, a combination of a ceramic sleeve and a D-shaped ceramic ferrule is adopted to install the lead-in fiber, as can be seen in Fig. 2(b). The ceramic sleeve has an outer diameter of 2.5 mm which matches the size of the circular groove, and inner diameter of 1.25 mm is selected according to the ferrule diameter. In order to balance the pressure inside and outside the cavity, the initial cylindrical ceramic ferrule is polished along the Z-axis to form a D-shaped section view in the XY-plane. As cavity and cylindric ferrule are concentric while the diameters are 1 mm and 1.25 mm respectively, the open cavity hole can be formed as long as the radial polishing distance is larger than 0.125 mm. In our design, the polishing distance on the radial direction in XY-plane is set to 0.2 mm and subsequently an open cavity hole of 0.075 mm is formed, as depicted by the zoom-in part of the sensor’s sectional view in Fig. 2(b). The lead-in single mode fiber (SMF) is inserted into the ferrule to deliver light to the diaphragm. The immobilizations between the sleeve and substrate, the ferrule and sleeve, SMF and the ferrule, are realized by epoxy resin. The real image of the sensor head is shown in Fig. 2(c). The size of the sensor is rather small with form factor no larger than 4 mm × 4 mm × 10 mm.

We measured the reflected optical spectrum of the assembled sensor. With the assist of the measured data, we can make an estimation on the reflectivity of the Si3N4-Ti composite film. The spatial frequency spectrum of the sensor (calculated from the optical spectrum which is shown by the inset) is shown by Fig. 3. From the spatial frequency spectrum, we can see that the main frequency peak is at 0.1 nm−1, which indicates an FSR of 10 nm in the optical spectrum. Therefore, we can roughly estimate that the cavity length of the sensor is about 120 μm. According to Eq. (3) and simulation result in Fig. 1, the roundtrip transmission coefficient in the cavity can be calculated to be 16% (loss of 84%). Then the fringe contrast at around 1550 nm is measured to be 25.7 dB, as indicated in the inset of Fig. 3. Combined the spatial cavity loss, fringe contrast, and the copper-coated fiber end reflection, the reflectivity of the composite diaphragm is estimated to be about 55%.

 

Fig. 3 Spatial frequency spectrum of the sensor and the reflected optical spectrum (inset).

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3. Experimental results and analysis

The sensor response to low-frequency acoustic wave is then measured using the setup demonstrated by Fig. 4. A low-frequency comparison coupler (B&K WB-3570) is employed as the sound source. The maximum acoustic frequency that the coupler can provide is 251 Hz. Our assembled EFPI sensor and a reference microphone (B&K 4193-L-004) are both inserted into the coupler to expose to the same sound field. For the EFPI sensor signal readout, we adopted a white light interferometry (WLI) phase demodulation algorithm that reported in our previous work [30]. In order to apply this algorithm to dynamic signal, an FBGA interrogator is applied here to collect the sensor’s optical spectrum data. A broadband amplified spontaneous emission (ASE) source is adopted to illuminate the EFPI sensor. The reflected light from the sensor is delivered into the interrogator, wherein the beam is firstly shaped by lens and then diffracted by a volume phase grating (VPG), after which optical beams with different wavelengths are diffracted and spatially separated, so that optical intensity of each wavelength is detected by a specific pixel on the InGaAs sensor array. Under this principle, at each sampling time tS, a group of optical spectrum data [{λS1, λS2… λSn}, {IS1, IS2… ISn}] is obtained and electronically output for WLI algorithm processing. The sampling frequency is 5 kHz in the experiment. The algorithm analyzes the optical spectrum data in the Fourier domain and computes the phase of the sensor’s spatial frequency component (determined by the cavity length) at tS. Since the acoustic wave will introduce phase modulation to the reflected optical beam, the acoustic waveform can be expressed by the phase signal computed from the WLI algorithm. Compared with voltage output signals from conventional edge-filtered intensity demodulation [11,12], the phase signal (cavity length) from the WLI algorithm can present the sensitivity characteristics of the sensor itself much more directly.

 

Fig. 4 Schematic diagram of low-frequency measurement setup.

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In the experiment, acoustic waves with frequencies ranging from 0.1 Hz to 250 Hz are applied to the sensor. Output signals are demodulated through the WLI phase demodulation algorithm and frequency analysis is performed by the fast Fourier transform (FFT). Frequency spectra of demodulated signals at different frequencies are plotted in Fig. 5. In the figure we can see that signals with frequencies ranging from 0.1 Hz to 250 Hz can all be distinguished, indicates that the sensor can well respond to low-frequency acoustic waves within this frequency range and signals can be correctly demodulated. It is noteworthy that since the sound pressure values of acoustic waves at different frequencies are not all the same in the test, the peak intensities at different frequencies are varying in the FFT spectra in Fig. 5. The details will be given in the following part.

 

Fig. 5 Frequency spectra of sensor output signals under exposure to acoustic waves from 0.1 Hz to 250 Hz.

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In order to acquire the frequency response characterization of the EFPI sensor, we calculate the phase sensitivities at diverse frequencies. The acoustic pressure of sound field at each frequency in our measurement is calibrated by the reference microphone B&K 4193-L-004, and the data is given out as the black dots in Fig. 8. To obtain the amplitudes of time-domain phase signals that demodulated by the WLI algorithm, we employ the sinusoidal fitting method rather than searching the maximum and minimum values, since the amplitude computed from the latter will be more easily affected by the noise and subsequently degrade the accuracy. The fitting is conducted by the first-order sine fitting model in matlab, and the fitting function is expressed by Eq. (4). In the fitting equation, a indicates the amplitude of the fitted time-domain phase signal P. Since the sine fitting model considers no direct current (DC) component, the DC value of the demodulated signal is firstly eliminated before the fitting procedure. The DC value is estimated by averaging of all sampling values. Phase sensitivity can be computed from the fitting parameter according to Eq. (5), and p0 refers to the sound pressure. The sensitivity is presented in logarithmic scale with a reference sensitivity of 1 rad/μPa.

P=asin(bt+c)
S(dB)=20log(ap0(1radμPa1))

Figures 6 and 7 exhibit the sensitivity characterization of the sensor obtained from the time-domain signal data fitting. Figures 6(a)–6(d) demonstrate the sampled point and data fitting curve of 0.1 Hz, 0.5 Hz, 20 Hz, and 50 Hz signals respectively. The computed WLI phase sensitivities at all measured frequencies are plotted as the blue dots in the inset of Fig. 7, through which the sensor’s frequency response characteristic is clearly revealed. From the measured results we can observe that the sensor performs a rather flat response region in the frequency range from 0.5 Hz to 250 Hz with sensitivity fluctuation no larger than 0.8 dB. Sensitivity decrease of the measured result at 0.1 Hz might come from the characteristic degradation of our calibration system (low-frequency comparison coupler and reference microphone) since 0.1 Hz is the lowest limiting frequency of the system according to the specifications. We also conducted simulation on the frequency response (film deformation to acoustic pressure) of the proposed sensor, as shown by the red curve in Fig. 7. Since the sensing diaphragm is a composite structure of silicon nitride and titanium, effective Young’s modulus and Poisson’s ratio should be calculated before the simulation. The two parameters of the composite film can be obtained from the rule of mixtures shown in Eq. (6) and Eq. (7) [31]. In the equations, Ec, μc, and hc are the Young’s modulus, Poisson’s ratio, and thickness of the composite diaphragm, while Ei, μi, and hi are parameters for each layer (i = 1, 2, corresponding to silicon nitride layer and titanium layer, respectively). Young’s modulus of silicon nitride layer and titanium are 300 GPa and 116 GPa, while Poisson’s ratio values are 0.28 and 0.34 for the two materials, respectively. Simulation result indicates that the sensor shows a resonant frequency at about 26 kHz, which is relative high due to our diaphragm design. Benefit from this, the sensor achieves a good response flatness in the low-frequency range.

 

Fig. 6 Sinusoidal fitting of time domain signal (a) 0.1 Hz; (b) 0.5 Hz; (c) 20 Hz; (d) 50 Hz.

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Fig. 7 Measured (blue dots) and simulated (red curve) sensor’s frequency response of acoustic sensitivity.

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Echc1μc2=E1h11μ12+E2h21μ22
μchc=μ1h1+μ2h2

We also investigate on the equivalent noise pressure of the sensor from our measurement results. As in Fig. 8, the black dots indicate the sound pressure calibrated by the reference microphone, while red dots are the signal to noise ratio (SNR) that can be obtained from the FFT spectra shown in Fig. 5. According to our previous work [32], we derived and proved that the signal frequency peak intensity (dB) in the spatial frequency domain is proportional to the sound pressure (dB) and the linear coefficient is 1. That means, in the FFT spectra, if the sound pressure is decreased by the value that equals to the SNR, the peak intensity will drop to the noise level. Under this principle, we estimate the equivalent noise pressure of our measured signals at each frequency according to the sound pressure and SNR, and is plotted by the blue dots in Fig. 8. It can be seen that the noise level follows a reasonable tendency of 1/f curve. In the frequency range larger than 5 Hz, the noise level is rather low around 40 dB (2 mPa) referenced by 20 μPa.

 

Fig. 8 SNR and equivalent noise pressure of measured sensor output signals at different frequencies.

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Furthermore, in order to prove the potentials of extending the applications of proposed sensor to underwater environment, we put forward a water pressure test on the sensor to monitor the sensor’s optical spectrum before and after applying pressure. The results are exhibited by Fig. 9. In the pressure test the sensor is placed inside a water pressure tank without any protection. The water pressure is rapidly increased from standard atmosphere pressure (0.1 MPa) to 25 MPa (equals to 250 times of standard atmosphere pressure, or pressure at 2500 m water depth) and then maintain at 25 MPa for 20 minutes. After the pressure maintaining test, the optical spectrum of the sensor is measured. The sensor spectra before and after applying 25 MPa water pressure are plotted in Fig. 9(a). From the figure we can observe that the optical spectrum stays almost the same before and after the high-pressure applying procedure, and the contrast still remains higher than 25 dB, indicating that the diaphragm of the EFPI cavity is not damaged and is still functioning well. This proves that the diaphragm can bear either high environmental pressure or large and rapid pressure variations, benefit from the designed open cavity structure. Another noteworthy point is that very little phase shift of the spectrum can be observed from Fig. 9(a), and we believe that this is caused by the little amount of residual water that stays in the cavity after the sensor is taken out from the tank. Furthermore, we also measured the sensor’s spectrum when immersed in water, as shown in Fig. 9(b). Compared with the spectrum in air, the FSR decreased to about 7 nm, indicating that the water flows into and fills the cavity through the open cavity hole and thus increasing the optical path difference. Meanwhile, the spectrum still performs a fringe contrast of about 15 dB, which is enough for the WLI phase demodulation. The degradation of the fringe contrast underwater is owing to the power mismatch between the two reflected beams, which is caused by both the reflectivity variation and spatial loss increase due to the filled water in the cavity. Since the WLI algorithm will track the sensor spatial frequency, so the FSR variation of the sensor underwater will not affect the phase demodulation.

 

Fig. 9 (a) Measured sensor’s optical spectrum in air before and after applying 25 MPa water pressure; (b) optical spectrum of the sensor under water.

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4. Summary

To summarize, we proposed a compact EFPI sensor structure based on micromachining techniques for low-frequency acoustic wave sensing. Sensor response to 0.1 - 250 Hz acoustic wave is exhibited, and a flat sensitivity response region within 0.5 – 250 Hz is achieved. The sensitivity fluctuation is limited within 0.8 dB. Due to our specific design of the diaphragm and sensor assembling structure, the proposed sensor exhibits good resistant ability to both high pressure and water environment, which gives the sensor significant potential for applications in harsh environments of high pressure, humidity, or even underwater, such as hydrophone, pipeline or downhole situations, etc.

Funding

National Key R&D Program of China (2018YFF01011800); National Natural Science Foundation of China (61775070); Fundamental Research Funds for the Central Universities (2017KFYXJJ032, 2019kfyXMBZ052).

References

1. A. Schimmel and J. Hübl, “Automatic detection of debris flows and debris floods based on a combination of infrasound and seismic signals,” Landslides 13(5), 1181–1196 (2016). [CrossRef]  

2. R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

3. Y. Xia, J. Liu, X. Cui, J. Li, W. Chen, and C. Liu, “Abnormal infrasound signals before 92 M ≧ 7.0 worldwide earthquakes during 2002–2008,” J. Asian Earth Sci. 41(4-5), 434–441 (2011). [CrossRef]  

4. C. Talmadge, “Infrasound and low frequency sound emitted from tornados,” J. Acoust. Soc. Am. 141(5), 3567 (2017). [CrossRef]  

5. Q. Xu, L. Zhang, and W. Liang, “Acoustic detection technology for gas pipeline leakage,” Process Saf. Environ. 91(4), 253–261 (2013). [CrossRef]  

6. J. Xu, L. Headings, and M. Dapino, “High sensitivity polyvinylidene fluoride microphone based on area ratio amplification and minimal capacitance,” IEEE Sens. J. 15(5), 2839–2847 (2015).

7. N. Ledermann, P. Muralt, J. Baborowski, M. Forster, and J. Pellaux, “Piezoelectric Pb (Zrx, Ti1− x) O3 thin film cantilever and bridge acoustic sensors for miniaturized photoacoustic gas detectors,” J. Micromech. Microeng. 14(12), 1650–1658 (2004). [CrossRef]  

8. J. Ma, M. Zhao, X. Huang, H. Bae, Y. Chen, and M. Yu, “Low cost, high performance white-light fiber-optic hydrophone system with a trackable working point,” Opt. Express 24(17), 19008–19019 (2016). [CrossRef]   [PubMed]  

9. X. Wang, L. Jin, J. Li, Y. Ran, and B. O. Guan, “Microfiber interferometric acoustic transducers,” Opt. Express 22(7), 8126–8135 (2014). [CrossRef]   [PubMed]  

10. D. Pawar, C. N. Rao, R. K. Choubey, and S. N. Kale, “Mach-Zehnder interferometric photonic crystal fiber for low acoustic frequency detections,” Appl. Phys. Lett. 108(4), 041912 (2016). [CrossRef]  

11. Y. Zhao, M. Chen, F. Xia, and R. Lv, “Small in-fiber Fabry-Perot low-frequency acoustic pressure sensor with PDMS diaphragm embedded in hollow-core fiber,” Sensor. Actuat. A 270, 162–169 (2018). [CrossRef]  

12. Z. Gong, K. Chen, X. Zhou, Y. Yang, Z. Zhao, H. Zou, and Q. Yu, “High-sensitivity Fabry-Perot interferometric acoustic sensor for low-frequency acoustic pressure detections,” J. Lightwave Technol. 35(24), 5276–5279 (2017). [CrossRef]  

13. W. Ni, P. Lu, X. Fu, W. Zhang, P. P. Shum, H. Sun, C. Yang, D. Liu, and J. Zhang, “Ultrathin graphene diaphragm-based extrinsic Fabry-Perot interferometer for ultra-wideband fiber optic acoustic sensing,” Opt. Express 26(16), 20758–20767 (2018). [CrossRef]   [PubMed]  

14. L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016). [CrossRef]  

15. K. Chen, Z. Yu, Q. Yu, M. Guo, Z. Zhao, C. Qu, Z. Gong, and Y. Yang, “Fast demodulated white-light interferometry-based fiber-optic Fabry-Perot cantilever microphone,” Opt. Lett. 43(14), 3417–3420 (2018). [CrossRef]   [PubMed]  

16. B. Liu, J. Lin, H. Liu, Y. Ma, L. Yan, and P. Jin, “Diaphragm based long cavity Fabry–Perot fiber acoustic sensor using phase generated carrier,” Opt. Commun. 382, 514–518 (2017). [CrossRef]  

17. B. Liu, J. Lin, H. Liu, A. Jin, and P. Jin, “Extrinsic Fabry-Perot fiber acoustic pressure sensor based on large-area silver diaphragm,” Microelectron. Eng. 166, 50–54 (2016). [CrossRef]  

18. F. Wang, Z. Shao, J. Xie, Z. Hu, H. Luo, and Y. Hu, “Extrinsic Fabry–Pérot underwater acoustic sensor based on micromachined center-embossed diaphragm,” J. Lightwave Technol. 32(23), 4026–4034 (2014).

19. Q. Wu and Y. Okabe, “High-sensitivity ultrasonic phase-shifted fiber Bragg grating balanced sensing system,” Opt. Express 20(27), 28353–28362 (2012). [CrossRef]   [PubMed]  

20. Z. Li, Y. Tong, X. Fu, J. Wang, Q. Guo, H. Yu, and X. Bao, “Simultaneous distributed static and dynamic sensing based on ultra-short fiber Bragg gratings,” Opt. Express 26(13), 17437–17446 (2018). [CrossRef]   [PubMed]  

21. L. Hu, G. Liu, Y. Zhu, X. Luo, and M. Han, “Laser frequency noise cancelation in a phase-shifted fiber Bragg grating ultrasonic sensor system using a reference grating channel,” IEEE Photonics J. 8(1), 1–8 (2016). [CrossRef]  

22. J. O. Gaudron, F. Surre, T. Sun, and K. T. V. Grattan, “LPG-based optical fibre sensor for acoustic wave detection,” Sensor. Actuat. A 173(1), 97–101 (2012). [CrossRef]  

23. Y. Ju, W. Zhang, C. Yang, S. L. Zhang, X. Ding, S. T. Wang, H. Zhou, G. Y. Feng, and S. H. Zhou, “Displacement and acoustic vibration sensor based on gold nanobipyramids doped PDMS micro-fiber,” Opt. Express 26(24), 31889–31897 (2018). [CrossRef]   [PubMed]  

24. Y. H. Tseng and J. S. Wang, “Single-crystalline tellurite optical fiber hydrophone,” Opt. Lett. 41(5), 970–973 (2016). [CrossRef]   [PubMed]  

25. C. Lyu, C. Wu, H. Y. Tam, C. Lu, and J. Ma, “Polarimetric heterodyning fiber laser sensor for directional acoustic signal measurement,” Opt. Express 21(15), 18273–18280 (2013). [CrossRef]   [PubMed]  

26. M. Han, T. Liu, L. Hu, and Q. Zhang, “Intensity-demodulated fiber-ring laser sensor system for acoustic emission detection,” Opt. Express 21(24), 29269–29276 (2013). [CrossRef]   [PubMed]  

27. Z. Wang, W. Zhang, W. Huang, S. Feng, and F. Li, “Optoelectronic hybrid fiber laser sensor for simultaneous acoustic and magnetic measurement,” Opt. Express 23(19), 24383–24389 (2015). [CrossRef]   [PubMed]  

28. X. Bai, Y. Liang, H. Sun, L. Jin, J. Ma, B. O. Guan, and L. Wang, “Sensitivity characteristics of broadband fiber-laser-based ultrasound sensors for photoacoustic microscopy,” Opt. Express 25(15), 17616–17626 (2017). [CrossRef]   [PubMed]  

29. D. Marcuse, “Loss analysis of single-mode fiber splices,” Bell Syst. Tech. J. 56(5), 703–718 (1977). [CrossRef]  

30. X. Fu, P. Lu, W. Ni, H. Liao, D. Liu, and J. Zhang, “Phase demodulation of interferometric fiber sensor based on fast Fourier analysis,” Opt. Express 25(18), 21094–21106 (2017). [CrossRef]   [PubMed]  

31. B. Agarwal, L. Broutman, and K. Chandrashekhara, Analysis and performance of fiber composites (John Wiley & Sons, 2017).

32. X. Fu, P. Lu, W. Ni, H. Liao, X. Jiang, D. Liu, and J. Zhang, “Phase interrogation of diaphragm-based optical fiber acoustic sensor assisted by wavelength-scanned spectral coding,” IEEE Photonics J. 10(3), 1–11 (2018). [CrossRef]  

References

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  1. A. Schimmel and J. Hübl, “Automatic detection of debris flows and debris floods based on a combination of infrasound and seismic signals,” Landslides 13(5), 1181–1196 (2016).
    [Crossref]
  2. R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).
  3. Y. Xia, J. Liu, X. Cui, J. Li, W. Chen, and C. Liu, “Abnormal infrasound signals before 92 M ≧ 7.0 worldwide earthquakes during 2002–2008,” J. Asian Earth Sci. 41(4-5), 434–441 (2011).
    [Crossref]
  4. C. Talmadge, “Infrasound and low frequency sound emitted from tornados,” J. Acoust. Soc. Am. 141(5), 3567 (2017).
    [Crossref]
  5. Q. Xu, L. Zhang, and W. Liang, “Acoustic detection technology for gas pipeline leakage,” Process Saf. Environ. 91(4), 253–261 (2013).
    [Crossref]
  6. J. Xu, L. Headings, and M. Dapino, “High sensitivity polyvinylidene fluoride microphone based on area ratio amplification and minimal capacitance,” IEEE Sens. J. 15(5), 2839–2847 (2015).
  7. N. Ledermann, P. Muralt, J. Baborowski, M. Forster, and J. Pellaux, “Piezoelectric Pb (Zrx, Ti1− x) O3 thin film cantilever and bridge acoustic sensors for miniaturized photoacoustic gas detectors,” J. Micromech. Microeng. 14(12), 1650–1658 (2004).
    [Crossref]
  8. J. Ma, M. Zhao, X. Huang, H. Bae, Y. Chen, and M. Yu, “Low cost, high performance white-light fiber-optic hydrophone system with a trackable working point,” Opt. Express 24(17), 19008–19019 (2016).
    [Crossref] [PubMed]
  9. X. Wang, L. Jin, J. Li, Y. Ran, and B. O. Guan, “Microfiber interferometric acoustic transducers,” Opt. Express 22(7), 8126–8135 (2014).
    [Crossref] [PubMed]
  10. D. Pawar, C. N. Rao, R. K. Choubey, and S. N. Kale, “Mach-Zehnder interferometric photonic crystal fiber for low acoustic frequency detections,” Appl. Phys. Lett. 108(4), 041912 (2016).
    [Crossref]
  11. Y. Zhao, M. Chen, F. Xia, and R. Lv, “Small in-fiber Fabry-Perot low-frequency acoustic pressure sensor with PDMS diaphragm embedded in hollow-core fiber,” Sensor. Actuat. A 270, 162–169 (2018).
    [Crossref]
  12. Z. Gong, K. Chen, X. Zhou, Y. Yang, Z. Zhao, H. Zou, and Q. Yu, “High-sensitivity Fabry-Perot interferometric acoustic sensor for low-frequency acoustic pressure detections,” J. Lightwave Technol. 35(24), 5276–5279 (2017).
    [Crossref]
  13. W. Ni, P. Lu, X. Fu, W. Zhang, P. P. Shum, H. Sun, C. Yang, D. Liu, and J. Zhang, “Ultrathin graphene diaphragm-based extrinsic Fabry-Perot interferometer for ultra-wideband fiber optic acoustic sensing,” Opt. Express 26(16), 20758–20767 (2018).
    [Crossref] [PubMed]
  14. L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
    [Crossref]
  15. K. Chen, Z. Yu, Q. Yu, M. Guo, Z. Zhao, C. Qu, Z. Gong, and Y. Yang, “Fast demodulated white-light interferometry-based fiber-optic Fabry-Perot cantilever microphone,” Opt. Lett. 43(14), 3417–3420 (2018).
    [Crossref] [PubMed]
  16. B. Liu, J. Lin, H. Liu, Y. Ma, L. Yan, and P. Jin, “Diaphragm based long cavity Fabry–Perot fiber acoustic sensor using phase generated carrier,” Opt. Commun. 382, 514–518 (2017).
    [Crossref]
  17. B. Liu, J. Lin, H. Liu, A. Jin, and P. Jin, “Extrinsic Fabry-Perot fiber acoustic pressure sensor based on large-area silver diaphragm,” Microelectron. Eng. 166, 50–54 (2016).
    [Crossref]
  18. F. Wang, Z. Shao, J. Xie, Z. Hu, H. Luo, and Y. Hu, “Extrinsic Fabry–Pérot underwater acoustic sensor based on micromachined center-embossed diaphragm,” J. Lightwave Technol. 32(23), 4026–4034 (2014).
  19. Q. Wu and Y. Okabe, “High-sensitivity ultrasonic phase-shifted fiber Bragg grating balanced sensing system,” Opt. Express 20(27), 28353–28362 (2012).
    [Crossref] [PubMed]
  20. Z. Li, Y. Tong, X. Fu, J. Wang, Q. Guo, H. Yu, and X. Bao, “Simultaneous distributed static and dynamic sensing based on ultra-short fiber Bragg gratings,” Opt. Express 26(13), 17437–17446 (2018).
    [Crossref] [PubMed]
  21. L. Hu, G. Liu, Y. Zhu, X. Luo, and M. Han, “Laser frequency noise cancelation in a phase-shifted fiber Bragg grating ultrasonic sensor system using a reference grating channel,” IEEE Photonics J. 8(1), 1–8 (2016).
    [Crossref]
  22. J. O. Gaudron, F. Surre, T. Sun, and K. T. V. Grattan, “LPG-based optical fibre sensor for acoustic wave detection,” Sensor. Actuat. A 173(1), 97–101 (2012).
    [Crossref]
  23. Y. Ju, W. Zhang, C. Yang, S. L. Zhang, X. Ding, S. T. Wang, H. Zhou, G. Y. Feng, and S. H. Zhou, “Displacement and acoustic vibration sensor based on gold nanobipyramids doped PDMS micro-fiber,” Opt. Express 26(24), 31889–31897 (2018).
    [Crossref] [PubMed]
  24. Y. H. Tseng and J. S. Wang, “Single-crystalline tellurite optical fiber hydrophone,” Opt. Lett. 41(5), 970–973 (2016).
    [Crossref] [PubMed]
  25. C. Lyu, C. Wu, H. Y. Tam, C. Lu, and J. Ma, “Polarimetric heterodyning fiber laser sensor for directional acoustic signal measurement,” Opt. Express 21(15), 18273–18280 (2013).
    [Crossref] [PubMed]
  26. M. Han, T. Liu, L. Hu, and Q. Zhang, “Intensity-demodulated fiber-ring laser sensor system for acoustic emission detection,” Opt. Express 21(24), 29269–29276 (2013).
    [Crossref] [PubMed]
  27. Z. Wang, W. Zhang, W. Huang, S. Feng, and F. Li, “Optoelectronic hybrid fiber laser sensor for simultaneous acoustic and magnetic measurement,” Opt. Express 23(19), 24383–24389 (2015).
    [Crossref] [PubMed]
  28. X. Bai, Y. Liang, H. Sun, L. Jin, J. Ma, B. O. Guan, and L. Wang, “Sensitivity characteristics of broadband fiber-laser-based ultrasound sensors for photoacoustic microscopy,” Opt. Express 25(15), 17616–17626 (2017).
    [Crossref] [PubMed]
  29. D. Marcuse, “Loss analysis of single-mode fiber splices,” Bell Syst. Tech. J. 56(5), 703–718 (1977).
    [Crossref]
  30. X. Fu, P. Lu, W. Ni, H. Liao, D. Liu, and J. Zhang, “Phase demodulation of interferometric fiber sensor based on fast Fourier analysis,” Opt. Express 25(18), 21094–21106 (2017).
    [Crossref] [PubMed]
  31. B. Agarwal, L. Broutman, and K. Chandrashekhara, Analysis and performance of fiber composites (John Wiley & Sons, 2017).
  32. X. Fu, P. Lu, W. Ni, H. Liao, X. Jiang, D. Liu, and J. Zhang, “Phase interrogation of diaphragm-based optical fiber acoustic sensor assisted by wavelength-scanned spectral coding,” IEEE Photonics J. 10(3), 1–11 (2018).
    [Crossref]

2018 (7)

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Y. Zhao, M. Chen, F. Xia, and R. Lv, “Small in-fiber Fabry-Perot low-frequency acoustic pressure sensor with PDMS diaphragm embedded in hollow-core fiber,” Sensor. Actuat. A 270, 162–169 (2018).
[Crossref]

K. Chen, Z. Yu, Q. Yu, M. Guo, Z. Zhao, C. Qu, Z. Gong, and Y. Yang, “Fast demodulated white-light interferometry-based fiber-optic Fabry-Perot cantilever microphone,” Opt. Lett. 43(14), 3417–3420 (2018).
[Crossref] [PubMed]

W. Ni, P. Lu, X. Fu, W. Zhang, P. P. Shum, H. Sun, C. Yang, D. Liu, and J. Zhang, “Ultrathin graphene diaphragm-based extrinsic Fabry-Perot interferometer for ultra-wideband fiber optic acoustic sensing,” Opt. Express 26(16), 20758–20767 (2018).
[Crossref] [PubMed]

Z. Li, Y. Tong, X. Fu, J. Wang, Q. Guo, H. Yu, and X. Bao, “Simultaneous distributed static and dynamic sensing based on ultra-short fiber Bragg gratings,” Opt. Express 26(13), 17437–17446 (2018).
[Crossref] [PubMed]

Y. Ju, W. Zhang, C. Yang, S. L. Zhang, X. Ding, S. T. Wang, H. Zhou, G. Y. Feng, and S. H. Zhou, “Displacement and acoustic vibration sensor based on gold nanobipyramids doped PDMS micro-fiber,” Opt. Express 26(24), 31889–31897 (2018).
[Crossref] [PubMed]

X. Fu, P. Lu, W. Ni, H. Liao, X. Jiang, D. Liu, and J. Zhang, “Phase interrogation of diaphragm-based optical fiber acoustic sensor assisted by wavelength-scanned spectral coding,” IEEE Photonics J. 10(3), 1–11 (2018).
[Crossref]

2017 (5)

2016 (7)

J. Ma, M. Zhao, X. Huang, H. Bae, Y. Chen, and M. Yu, “Low cost, high performance white-light fiber-optic hydrophone system with a trackable working point,” Opt. Express 24(17), 19008–19019 (2016).
[Crossref] [PubMed]

A. Schimmel and J. Hübl, “Automatic detection of debris flows and debris floods based on a combination of infrasound and seismic signals,” Landslides 13(5), 1181–1196 (2016).
[Crossref]

D. Pawar, C. N. Rao, R. K. Choubey, and S. N. Kale, “Mach-Zehnder interferometric photonic crystal fiber for low acoustic frequency detections,” Appl. Phys. Lett. 108(4), 041912 (2016).
[Crossref]

B. Liu, J. Lin, H. Liu, A. Jin, and P. Jin, “Extrinsic Fabry-Perot fiber acoustic pressure sensor based on large-area silver diaphragm,” Microelectron. Eng. 166, 50–54 (2016).
[Crossref]

Y. H. Tseng and J. S. Wang, “Single-crystalline tellurite optical fiber hydrophone,” Opt. Lett. 41(5), 970–973 (2016).
[Crossref] [PubMed]

L. Hu, G. Liu, Y. Zhu, X. Luo, and M. Han, “Laser frequency noise cancelation in a phase-shifted fiber Bragg grating ultrasonic sensor system using a reference grating channel,” IEEE Photonics J. 8(1), 1–8 (2016).
[Crossref]

L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
[Crossref]

2015 (2)

Z. Wang, W. Zhang, W. Huang, S. Feng, and F. Li, “Optoelectronic hybrid fiber laser sensor for simultaneous acoustic and magnetic measurement,” Opt. Express 23(19), 24383–24389 (2015).
[Crossref] [PubMed]

J. Xu, L. Headings, and M. Dapino, “High sensitivity polyvinylidene fluoride microphone based on area ratio amplification and minimal capacitance,” IEEE Sens. J. 15(5), 2839–2847 (2015).

2014 (2)

2013 (3)

2012 (2)

J. O. Gaudron, F. Surre, T. Sun, and K. T. V. Grattan, “LPG-based optical fibre sensor for acoustic wave detection,” Sensor. Actuat. A 173(1), 97–101 (2012).
[Crossref]

Q. Wu and Y. Okabe, “High-sensitivity ultrasonic phase-shifted fiber Bragg grating balanced sensing system,” Opt. Express 20(27), 28353–28362 (2012).
[Crossref] [PubMed]

2011 (1)

Y. Xia, J. Liu, X. Cui, J. Li, W. Chen, and C. Liu, “Abnormal infrasound signals before 92 M ≧ 7.0 worldwide earthquakes during 2002–2008,” J. Asian Earth Sci. 41(4-5), 434–441 (2011).
[Crossref]

2004 (1)

N. Ledermann, P. Muralt, J. Baborowski, M. Forster, and J. Pellaux, “Piezoelectric Pb (Zrx, Ti1− x) O3 thin film cantilever and bridge acoustic sensors for miniaturized photoacoustic gas detectors,” J. Micromech. Microeng. 14(12), 1650–1658 (2004).
[Crossref]

1977 (1)

D. Marcuse, “Loss analysis of single-mode fiber splices,” Bell Syst. Tech. J. 56(5), 703–718 (1977).
[Crossref]

Baborowski, J.

N. Ledermann, P. Muralt, J. Baborowski, M. Forster, and J. Pellaux, “Piezoelectric Pb (Zrx, Ti1− x) O3 thin film cantilever and bridge acoustic sensors for miniaturized photoacoustic gas detectors,” J. Micromech. Microeng. 14(12), 1650–1658 (2004).
[Crossref]

Bae, H.

Bai, X.

Bao, X.

Ceranna, L.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Chen, K.

Chen, M.

Y. Zhao, M. Chen, F. Xia, and R. Lv, “Small in-fiber Fabry-Perot low-frequency acoustic pressure sensor with PDMS diaphragm embedded in hollow-core fiber,” Sensor. Actuat. A 270, 162–169 (2018).
[Crossref]

Chen, W.

Y. Xia, J. Liu, X. Cui, J. Li, W. Chen, and C. Liu, “Abnormal infrasound signals before 92 M ≧ 7.0 worldwide earthquakes during 2002–2008,” J. Asian Earth Sci. 41(4-5), 434–441 (2011).
[Crossref]

Chen, Y.

Choubey, R. K.

D. Pawar, C. N. Rao, R. K. Choubey, and S. N. Kale, “Mach-Zehnder interferometric photonic crystal fiber for low acoustic frequency detections,” Appl. Phys. Lett. 108(4), 041912 (2016).
[Crossref]

Cui, X.

Y. Xia, J. Liu, X. Cui, J. Li, W. Chen, and C. Liu, “Abnormal infrasound signals before 92 M ≧ 7.0 worldwide earthquakes during 2002–2008,” J. Asian Earth Sci. 41(4-5), 434–441 (2011).
[Crossref]

Dapino, M.

J. Xu, L. Headings, and M. Dapino, “High sensitivity polyvinylidene fluoride microphone based on area ratio amplification and minimal capacitance,” IEEE Sens. J. 15(5), 2839–2847 (2015).

Ding, X.

Fee, D.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Feng, G. Y.

Feng, S.

Forster, M.

N. Ledermann, P. Muralt, J. Baborowski, M. Forster, and J. Pellaux, “Piezoelectric Pb (Zrx, Ti1− x) O3 thin film cantilever and bridge acoustic sensors for miniaturized photoacoustic gas detectors,” J. Micromech. Microeng. 14(12), 1650–1658 (2004).
[Crossref]

Franco, L.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Fu, X.

Gaudron, J. O.

J. O. Gaudron, F. Surre, T. Sun, and K. T. V. Grattan, “LPG-based optical fibre sensor for acoustic wave detection,” Sensor. Actuat. A 173(1), 97–101 (2012).
[Crossref]

Gong, Z.

Grattan, K. T. V.

J. O. Gaudron, F. Surre, T. Sun, and K. T. V. Grattan, “LPG-based optical fibre sensor for acoustic wave detection,” Sensor. Actuat. A 173(1), 97–101 (2012).
[Crossref]

Green, D.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Guan, B. O.

Guo, M.

Guo, Q.

Han, M.

L. Hu, G. Liu, Y. Zhu, X. Luo, and M. Han, “Laser frequency noise cancelation in a phase-shifted fiber Bragg grating ultrasonic sensor system using a reference grating channel,” IEEE Photonics J. 8(1), 1–8 (2016).
[Crossref]

M. Han, T. Liu, L. Hu, and Q. Zhang, “Intensity-demodulated fiber-ring laser sensor system for acoustic emission detection,” Opt. Express 21(24), 29269–29276 (2013).
[Crossref] [PubMed]

Haney, M.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Headings, L.

J. Xu, L. Headings, and M. Dapino, “High sensitivity polyvinylidene fluoride microphone based on area ratio amplification and minimal capacitance,” IEEE Sens. J. 15(5), 2839–2847 (2015).

Hu, L.

L. Hu, G. Liu, Y. Zhu, X. Luo, and M. Han, “Laser frequency noise cancelation in a phase-shifted fiber Bragg grating ultrasonic sensor system using a reference grating channel,” IEEE Photonics J. 8(1), 1–8 (2016).
[Crossref]

M. Han, T. Liu, L. Hu, and Q. Zhang, “Intensity-demodulated fiber-ring laser sensor system for acoustic emission detection,” Opt. Express 21(24), 29269–29276 (2013).
[Crossref] [PubMed]

Hu, Y.

Hu, Z.

Huang, W.

Huang, X.

Hübl, J.

A. Schimmel and J. Hübl, “Automatic detection of debris flows and debris floods based on a combination of infrasound and seismic signals,” Landslides 13(5), 1181–1196 (2016).
[Crossref]

Jiang, X.

X. Fu, P. Lu, W. Ni, H. Liao, X. Jiang, D. Liu, and J. Zhang, “Phase interrogation of diaphragm-based optical fiber acoustic sensor assisted by wavelength-scanned spectral coding,” IEEE Photonics J. 10(3), 1–11 (2018).
[Crossref]

Jin, A.

B. Liu, J. Lin, H. Liu, A. Jin, and P. Jin, “Extrinsic Fabry-Perot fiber acoustic pressure sensor based on large-area silver diaphragm,” Microelectron. Eng. 166, 50–54 (2016).
[Crossref]

Jin, L.

Jin, P.

B. Liu, J. Lin, H. Liu, Y. Ma, L. Yan, and P. Jin, “Diaphragm based long cavity Fabry–Perot fiber acoustic sensor using phase generated carrier,” Opt. Commun. 382, 514–518 (2017).
[Crossref]

B. Liu, J. Lin, H. Liu, A. Jin, and P. Jin, “Extrinsic Fabry-Perot fiber acoustic pressure sensor based on large-area silver diaphragm,” Microelectron. Eng. 166, 50–54 (2016).
[Crossref]

Ju, Y.

Kale, S. N.

D. Pawar, C. N. Rao, R. K. Choubey, and S. N. Kale, “Mach-Zehnder interferometric photonic crystal fiber for low acoustic frequency detections,” Appl. Phys. Lett. 108(4), 041912 (2016).
[Crossref]

Kelley, M.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Le Pichon, A.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Ledermann, N.

N. Ledermann, P. Muralt, J. Baborowski, M. Forster, and J. Pellaux, “Piezoelectric Pb (Zrx, Ti1− x) O3 thin film cantilever and bridge acoustic sensors for miniaturized photoacoustic gas detectors,” J. Micromech. Microeng. 14(12), 1650–1658 (2004).
[Crossref]

Li, F.

Li, J.

X. Wang, L. Jin, J. Li, Y. Ran, and B. O. Guan, “Microfiber interferometric acoustic transducers,” Opt. Express 22(7), 8126–8135 (2014).
[Crossref] [PubMed]

Y. Xia, J. Liu, X. Cui, J. Li, W. Chen, and C. Liu, “Abnormal infrasound signals before 92 M ≧ 7.0 worldwide earthquakes during 2002–2008,” J. Asian Earth Sci. 41(4-5), 434–441 (2011).
[Crossref]

Li, Z.

Liang, W.

Q. Xu, L. Zhang, and W. Liang, “Acoustic detection technology for gas pipeline leakage,” Process Saf. Environ. 91(4), 253–261 (2013).
[Crossref]

Liang, Y.

Liao, H.

X. Fu, P. Lu, W. Ni, H. Liao, X. Jiang, D. Liu, and J. Zhang, “Phase interrogation of diaphragm-based optical fiber acoustic sensor assisted by wavelength-scanned spectral coding,” IEEE Photonics J. 10(3), 1–11 (2018).
[Crossref]

X. Fu, P. Lu, W. Ni, H. Liao, D. Liu, and J. Zhang, “Phase demodulation of interferometric fiber sensor based on fast Fourier analysis,” Opt. Express 25(18), 21094–21106 (2017).
[Crossref] [PubMed]

Lin, J.

B. Liu, J. Lin, H. Liu, Y. Ma, L. Yan, and P. Jin, “Diaphragm based long cavity Fabry–Perot fiber acoustic sensor using phase generated carrier,” Opt. Commun. 382, 514–518 (2017).
[Crossref]

B. Liu, J. Lin, H. Liu, A. Jin, and P. Jin, “Extrinsic Fabry-Perot fiber acoustic pressure sensor based on large-area silver diaphragm,” Microelectron. Eng. 166, 50–54 (2016).
[Crossref]

Liu, B.

B. Liu, J. Lin, H. Liu, Y. Ma, L. Yan, and P. Jin, “Diaphragm based long cavity Fabry–Perot fiber acoustic sensor using phase generated carrier,” Opt. Commun. 382, 514–518 (2017).
[Crossref]

B. Liu, J. Lin, H. Liu, A. Jin, and P. Jin, “Extrinsic Fabry-Perot fiber acoustic pressure sensor based on large-area silver diaphragm,” Microelectron. Eng. 166, 50–54 (2016).
[Crossref]

Liu, C.

Y. Xia, J. Liu, X. Cui, J. Li, W. Chen, and C. Liu, “Abnormal infrasound signals before 92 M ≧ 7.0 worldwide earthquakes during 2002–2008,” J. Asian Earth Sci. 41(4-5), 434–441 (2011).
[Crossref]

Liu, D.

W. Ni, P. Lu, X. Fu, W. Zhang, P. P. Shum, H. Sun, C. Yang, D. Liu, and J. Zhang, “Ultrathin graphene diaphragm-based extrinsic Fabry-Perot interferometer for ultra-wideband fiber optic acoustic sensing,” Opt. Express 26(16), 20758–20767 (2018).
[Crossref] [PubMed]

X. Fu, P. Lu, W. Ni, H. Liao, X. Jiang, D. Liu, and J. Zhang, “Phase interrogation of diaphragm-based optical fiber acoustic sensor assisted by wavelength-scanned spectral coding,” IEEE Photonics J. 10(3), 1–11 (2018).
[Crossref]

X. Fu, P. Lu, W. Ni, H. Liao, D. Liu, and J. Zhang, “Phase demodulation of interferometric fiber sensor based on fast Fourier analysis,” Opt. Express 25(18), 21094–21106 (2017).
[Crossref] [PubMed]

L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
[Crossref]

Liu, G.

L. Hu, G. Liu, Y. Zhu, X. Luo, and M. Han, “Laser frequency noise cancelation in a phase-shifted fiber Bragg grating ultrasonic sensor system using a reference grating channel,” IEEE Photonics J. 8(1), 1–8 (2016).
[Crossref]

Liu, H.

B. Liu, J. Lin, H. Liu, Y. Ma, L. Yan, and P. Jin, “Diaphragm based long cavity Fabry–Perot fiber acoustic sensor using phase generated carrier,” Opt. Commun. 382, 514–518 (2017).
[Crossref]

B. Liu, J. Lin, H. Liu, A. Jin, and P. Jin, “Extrinsic Fabry-Perot fiber acoustic pressure sensor based on large-area silver diaphragm,” Microelectron. Eng. 166, 50–54 (2016).
[Crossref]

Liu, J.

Y. Xia, J. Liu, X. Cui, J. Li, W. Chen, and C. Liu, “Abnormal infrasound signals before 92 M ≧ 7.0 worldwide earthquakes during 2002–2008,” J. Asian Earth Sci. 41(4-5), 434–441 (2011).
[Crossref]

Liu, L.

L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
[Crossref]

Liu, T.

Lu, C.

Lu, P.

W. Ni, P. Lu, X. Fu, W. Zhang, P. P. Shum, H. Sun, C. Yang, D. Liu, and J. Zhang, “Ultrathin graphene diaphragm-based extrinsic Fabry-Perot interferometer for ultra-wideband fiber optic acoustic sensing,” Opt. Express 26(16), 20758–20767 (2018).
[Crossref] [PubMed]

X. Fu, P. Lu, W. Ni, H. Liao, X. Jiang, D. Liu, and J. Zhang, “Phase interrogation of diaphragm-based optical fiber acoustic sensor assisted by wavelength-scanned spectral coding,” IEEE Photonics J. 10(3), 1–11 (2018).
[Crossref]

X. Fu, P. Lu, W. Ni, H. Liao, D. Liu, and J. Zhang, “Phase demodulation of interferometric fiber sensor based on fast Fourier analysis,” Opt. Express 25(18), 21094–21106 (2017).
[Crossref] [PubMed]

L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
[Crossref]

Luo, H.

Luo, X.

L. Hu, G. Liu, Y. Zhu, X. Luo, and M. Han, “Laser frequency noise cancelation in a phase-shifted fiber Bragg grating ultrasonic sensor system using a reference grating channel,” IEEE Photonics J. 8(1), 1–8 (2016).
[Crossref]

Lv, R.

Y. Zhao, M. Chen, F. Xia, and R. Lv, “Small in-fiber Fabry-Perot low-frequency acoustic pressure sensor with PDMS diaphragm embedded in hollow-core fiber,” Sensor. Actuat. A 270, 162–169 (2018).
[Crossref]

Lyu, C.

Ma, J.

Ma, Y.

B. Liu, J. Lin, H. Liu, Y. Ma, L. Yan, and P. Jin, “Diaphragm based long cavity Fabry–Perot fiber acoustic sensor using phase generated carrier,” Opt. Commun. 382, 514–518 (2017).
[Crossref]

Marcuse, D.

D. Marcuse, “Loss analysis of single-mode fiber splices,” Bell Syst. Tech. J. 56(5), 703–718 (1977).
[Crossref]

Matoza, R.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

McKee, K.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Mikesell, T.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Muralt, P.

N. Ledermann, P. Muralt, J. Baborowski, M. Forster, and J. Pellaux, “Piezoelectric Pb (Zrx, Ti1− x) O3 thin film cantilever and bridge acoustic sensors for miniaturized photoacoustic gas detectors,” J. Micromech. Microeng. 14(12), 1650–1658 (2004).
[Crossref]

Ni, W.

Okabe, Y.

Pawar, D.

D. Pawar, C. N. Rao, R. K. Choubey, and S. N. Kale, “Mach-Zehnder interferometric photonic crystal fiber for low acoustic frequency detections,” Appl. Phys. Lett. 108(4), 041912 (2016).
[Crossref]

Pellaux, J.

N. Ledermann, P. Muralt, J. Baborowski, M. Forster, and J. Pellaux, “Piezoelectric Pb (Zrx, Ti1− x) O3 thin film cantilever and bridge acoustic sensors for miniaturized photoacoustic gas detectors,” J. Micromech. Microeng. 14(12), 1650–1658 (2004).
[Crossref]

Qu, C.

Ran, Y.

Rao, C. N.

D. Pawar, C. N. Rao, R. K. Choubey, and S. N. Kale, “Mach-Zehnder interferometric photonic crystal fiber for low acoustic frequency detections,” Appl. Phys. Lett. 108(4), 041912 (2016).
[Crossref]

Schimmel, A.

A. Schimmel and J. Hübl, “Automatic detection of debris flows and debris floods based on a combination of infrasound and seismic signals,” Landslides 13(5), 1181–1196 (2016).
[Crossref]

Shao, Z.

Shum, P. P.

Sun, H.

Sun, T.

J. O. Gaudron, F. Surre, T. Sun, and K. T. V. Grattan, “LPG-based optical fibre sensor for acoustic wave detection,” Sensor. Actuat. A 173(1), 97–101 (2012).
[Crossref]

Sun, Y.

L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
[Crossref]

Surre, F.

J. O. Gaudron, F. Surre, T. Sun, and K. T. V. Grattan, “LPG-based optical fibre sensor for acoustic wave detection,” Sensor. Actuat. A 173(1), 97–101 (2012).
[Crossref]

Talmadge, C.

C. Talmadge, “Infrasound and low frequency sound emitted from tornados,” J. Acoust. Soc. Am. 141(5), 3567 (2017).
[Crossref]

Tam, H. Y.

Tong, Y.

Tseng, Y. H.

Valderrama, O.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Vergoz, J.

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

Wang, F.

Wang, J.

Wang, J. S.

Wang, L.

Wang, S.

L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
[Crossref]

Wang, S. T.

Wang, X.

Wang, Z.

Wu, C.

Wu, Q.

Xia, F.

Y. Zhao, M. Chen, F. Xia, and R. Lv, “Small in-fiber Fabry-Perot low-frequency acoustic pressure sensor with PDMS diaphragm embedded in hollow-core fiber,” Sensor. Actuat. A 270, 162–169 (2018).
[Crossref]

Xia, Y.

Y. Xia, J. Liu, X. Cui, J. Li, W. Chen, and C. Liu, “Abnormal infrasound signals before 92 M ≧ 7.0 worldwide earthquakes during 2002–2008,” J. Asian Earth Sci. 41(4-5), 434–441 (2011).
[Crossref]

Xie, J.

Xu, H.

L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
[Crossref]

Xu, J.

J. Xu, L. Headings, and M. Dapino, “High sensitivity polyvinylidene fluoride microphone based on area ratio amplification and minimal capacitance,” IEEE Sens. J. 15(5), 2839–2847 (2015).

Xu, Q.

Q. Xu, L. Zhang, and W. Liang, “Acoustic detection technology for gas pipeline leakage,” Process Saf. Environ. 91(4), 253–261 (2013).
[Crossref]

Yan, L.

B. Liu, J. Lin, H. Liu, Y. Ma, L. Yan, and P. Jin, “Diaphragm based long cavity Fabry–Perot fiber acoustic sensor using phase generated carrier,” Opt. Commun. 382, 514–518 (2017).
[Crossref]

Yang, C.

Yang, Y.

Yao, Q.

L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
[Crossref]

Yu, H.

Yu, M.

Yu, Q.

Yu, Z.

Zhang, J.

W. Ni, P. Lu, X. Fu, W. Zhang, P. P. Shum, H. Sun, C. Yang, D. Liu, and J. Zhang, “Ultrathin graphene diaphragm-based extrinsic Fabry-Perot interferometer for ultra-wideband fiber optic acoustic sensing,” Opt. Express 26(16), 20758–20767 (2018).
[Crossref] [PubMed]

X. Fu, P. Lu, W. Ni, H. Liao, X. Jiang, D. Liu, and J. Zhang, “Phase interrogation of diaphragm-based optical fiber acoustic sensor assisted by wavelength-scanned spectral coding,” IEEE Photonics J. 10(3), 1–11 (2018).
[Crossref]

X. Fu, P. Lu, W. Ni, H. Liao, D. Liu, and J. Zhang, “Phase demodulation of interferometric fiber sensor based on fast Fourier analysis,” Opt. Express 25(18), 21094–21106 (2017).
[Crossref] [PubMed]

L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
[Crossref]

Zhang, L.

Q. Xu, L. Zhang, and W. Liang, “Acoustic detection technology for gas pipeline leakage,” Process Saf. Environ. 91(4), 253–261 (2013).
[Crossref]

Zhang, Q.

Zhang, S. L.

Zhang, W.

Zhao, M.

Zhao, Y.

Y. Zhao, M. Chen, F. Xia, and R. Lv, “Small in-fiber Fabry-Perot low-frequency acoustic pressure sensor with PDMS diaphragm embedded in hollow-core fiber,” Sensor. Actuat. A 270, 162–169 (2018).
[Crossref]

Zhao, Z.

Zhou, H.

Zhou, S. H.

Zhou, X.

Zhu, Y.

L. Hu, G. Liu, Y. Zhu, X. Luo, and M. Han, “Laser frequency noise cancelation in a phase-shifted fiber Bragg grating ultrasonic sensor system using a reference grating channel,” IEEE Photonics J. 8(1), 1–8 (2016).
[Crossref]

Zou, H.

Appl. Phys. Lett. (1)

D. Pawar, C. N. Rao, R. K. Choubey, and S. N. Kale, “Mach-Zehnder interferometric photonic crystal fiber for low acoustic frequency detections,” Appl. Phys. Lett. 108(4), 041912 (2016).
[Crossref]

Bell Syst. Tech. J. (1)

D. Marcuse, “Loss analysis of single-mode fiber splices,” Bell Syst. Tech. J. 56(5), 703–718 (1977).
[Crossref]

IEEE Photonics J. (3)

X. Fu, P. Lu, W. Ni, H. Liao, X. Jiang, D. Liu, and J. Zhang, “Phase interrogation of diaphragm-based optical fiber acoustic sensor assisted by wavelength-scanned spectral coding,” IEEE Photonics J. 10(3), 1–11 (2018).
[Crossref]

L. Hu, G. Liu, Y. Zhu, X. Luo, and M. Han, “Laser frequency noise cancelation in a phase-shifted fiber Bragg grating ultrasonic sensor system using a reference grating channel,” IEEE Photonics J. 8(1), 1–8 (2016).
[Crossref]

L. Liu, P. Lu, S. Wang, X. Fu, Y. Sun, D. Liu, J. Zhang, H. Xu, and Q. Yao, “UV adhesive diaphragm-based FPI sensor for very-low-frequency acoustic sensing,” IEEE Photonics J. 8(1), 1–9 (2016).
[Crossref]

IEEE Sens. J. (1)

J. Xu, L. Headings, and M. Dapino, “High sensitivity polyvinylidene fluoride microphone based on area ratio amplification and minimal capacitance,” IEEE Sens. J. 15(5), 2839–2847 (2015).

J. Acoust. Soc. Am. (1)

C. Talmadge, “Infrasound and low frequency sound emitted from tornados,” J. Acoust. Soc. Am. 141(5), 3567 (2017).
[Crossref]

J. Asian Earth Sci. (1)

Y. Xia, J. Liu, X. Cui, J. Li, W. Chen, and C. Liu, “Abnormal infrasound signals before 92 M ≧ 7.0 worldwide earthquakes during 2002–2008,” J. Asian Earth Sci. 41(4-5), 434–441 (2011).
[Crossref]

J. Geophys. Res-Sol. Ea. (1)

R. Matoza, D. Fee, D. Green, A. Le Pichon, J. Vergoz, M. Haney, T. Mikesell, L. Franco, O. Valderrama, M. Kelley, K. McKee, and L. Ceranna, “Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile,” J. Geophys. Res-Sol. Ea. 123(5), 3814–3827 (2018).

J. Lightwave Technol. (2)

J. Micromech. Microeng. (1)

N. Ledermann, P. Muralt, J. Baborowski, M. Forster, and J. Pellaux, “Piezoelectric Pb (Zrx, Ti1− x) O3 thin film cantilever and bridge acoustic sensors for miniaturized photoacoustic gas detectors,” J. Micromech. Microeng. 14(12), 1650–1658 (2004).
[Crossref]

Landslides (1)

A. Schimmel and J. Hübl, “Automatic detection of debris flows and debris floods based on a combination of infrasound and seismic signals,” Landslides 13(5), 1181–1196 (2016).
[Crossref]

Microelectron. Eng. (1)

B. Liu, J. Lin, H. Liu, A. Jin, and P. Jin, “Extrinsic Fabry-Perot fiber acoustic pressure sensor based on large-area silver diaphragm,” Microelectron. Eng. 166, 50–54 (2016).
[Crossref]

Opt. Commun. (1)

B. Liu, J. Lin, H. Liu, Y. Ma, L. Yan, and P. Jin, “Diaphragm based long cavity Fabry–Perot fiber acoustic sensor using phase generated carrier,” Opt. Commun. 382, 514–518 (2017).
[Crossref]

Opt. Express (11)

W. Ni, P. Lu, X. Fu, W. Zhang, P. P. Shum, H. Sun, C. Yang, D. Liu, and J. Zhang, “Ultrathin graphene diaphragm-based extrinsic Fabry-Perot interferometer for ultra-wideband fiber optic acoustic sensing,” Opt. Express 26(16), 20758–20767 (2018).
[Crossref] [PubMed]

J. Ma, M. Zhao, X. Huang, H. Bae, Y. Chen, and M. Yu, “Low cost, high performance white-light fiber-optic hydrophone system with a trackable working point,” Opt. Express 24(17), 19008–19019 (2016).
[Crossref] [PubMed]

X. Wang, L. Jin, J. Li, Y. Ran, and B. O. Guan, “Microfiber interferometric acoustic transducers,” Opt. Express 22(7), 8126–8135 (2014).
[Crossref] [PubMed]

X. Fu, P. Lu, W. Ni, H. Liao, D. Liu, and J. Zhang, “Phase demodulation of interferometric fiber sensor based on fast Fourier analysis,” Opt. Express 25(18), 21094–21106 (2017).
[Crossref] [PubMed]

Y. Ju, W. Zhang, C. Yang, S. L. Zhang, X. Ding, S. T. Wang, H. Zhou, G. Y. Feng, and S. H. Zhou, “Displacement and acoustic vibration sensor based on gold nanobipyramids doped PDMS micro-fiber,” Opt. Express 26(24), 31889–31897 (2018).
[Crossref] [PubMed]

Q. Wu and Y. Okabe, “High-sensitivity ultrasonic phase-shifted fiber Bragg grating balanced sensing system,” Opt. Express 20(27), 28353–28362 (2012).
[Crossref] [PubMed]

Z. Li, Y. Tong, X. Fu, J. Wang, Q. Guo, H. Yu, and X. Bao, “Simultaneous distributed static and dynamic sensing based on ultra-short fiber Bragg gratings,” Opt. Express 26(13), 17437–17446 (2018).
[Crossref] [PubMed]

C. Lyu, C. Wu, H. Y. Tam, C. Lu, and J. Ma, “Polarimetric heterodyning fiber laser sensor for directional acoustic signal measurement,” Opt. Express 21(15), 18273–18280 (2013).
[Crossref] [PubMed]

M. Han, T. Liu, L. Hu, and Q. Zhang, “Intensity-demodulated fiber-ring laser sensor system for acoustic emission detection,” Opt. Express 21(24), 29269–29276 (2013).
[Crossref] [PubMed]

Z. Wang, W. Zhang, W. Huang, S. Feng, and F. Li, “Optoelectronic hybrid fiber laser sensor for simultaneous acoustic and magnetic measurement,” Opt. Express 23(19), 24383–24389 (2015).
[Crossref] [PubMed]

X. Bai, Y. Liang, H. Sun, L. Jin, J. Ma, B. O. Guan, and L. Wang, “Sensitivity characteristics of broadband fiber-laser-based ultrasound sensors for photoacoustic microscopy,” Opt. Express 25(15), 17616–17626 (2017).
[Crossref] [PubMed]

Opt. Lett. (2)

Process Saf. Environ. (1)

Q. Xu, L. Zhang, and W. Liang, “Acoustic detection technology for gas pipeline leakage,” Process Saf. Environ. 91(4), 253–261 (2013).
[Crossref]

Sensor. Actuat. A (2)

Y. Zhao, M. Chen, F. Xia, and R. Lv, “Small in-fiber Fabry-Perot low-frequency acoustic pressure sensor with PDMS diaphragm embedded in hollow-core fiber,” Sensor. Actuat. A 270, 162–169 (2018).
[Crossref]

J. O. Gaudron, F. Surre, T. Sun, and K. T. V. Grattan, “LPG-based optical fibre sensor for acoustic wave detection,” Sensor. Actuat. A 173(1), 97–101 (2012).
[Crossref]

Other (1)

B. Agarwal, L. Broutman, and K. Chandrashekhara, Analysis and performance of fiber composites (John Wiley & Sons, 2017).

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Figures (9)

Fig. 1
Fig. 1 Simulation of transmission coefficient (blue curve) and loss (red curve) with air cavity length.
Fig. 2
Fig. 2 Schematic diagram of sensor fabrication process including (a) wafer micromachining; (b) sensor assembling; (c) sensor real image.
Fig. 3
Fig. 3 Spatial frequency spectrum of the sensor and the reflected optical spectrum (inset).
Fig. 4
Fig. 4 Schematic diagram of low-frequency measurement setup.
Fig. 5
Fig. 5 Frequency spectra of sensor output signals under exposure to acoustic waves from 0.1 Hz to 250 Hz.
Fig. 6
Fig. 6 Sinusoidal fitting of time domain signal (a) 0.1 Hz; (b) 0.5 Hz; (c) 20 Hz; (d) 50 Hz.
Fig. 7
Fig. 7 Measured (blue dots) and simulated (red curve) sensor’s frequency response of acoustic sensitivity.
Fig. 8
Fig. 8 SNR and equivalent noise pressure of measured sensor output signals at different frequencies.
Fig. 9
Fig. 9 (a) Measured sensor’s optical spectrum in air before and after applying 25 MPa water pressure; (b) optical spectrum of the sensor under water.

Equations (7)

Equations on this page are rendered with MathJax. Learn more.

{ η= 4(4 z 2 + w 1 2 w 2 2 ) (4 z 2 + w 1 2 + w 2 2 w 2 2 )+4 z 2 w 2 2 w 1 2 z= 2L n air k w 1 w 2 α=1η
w a =0.65+ 1.619 V 3/2 + 2.879 V 6 , V= 2πa λ n core 2 n clad 2
η= 1 1+ ( λL/ π w 2 ) 2
P=asin(bt+c)
S(dB)=20log( a p 0 (1 radμP a 1 ) )
E c h c 1 μ c 2 = E 1 h 1 1 μ 1 2 + E 2 h 2 1 μ 2 2
μ c h c = μ 1 h 1 + μ 2 h 2

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