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Abstract
A micro-fiber-optic acoustic sensor based on the high-quality-factor (high-Q) resonance effect that uses a Fabry-Pérot etalon (FPE) is presented in this study. The device has been demonstrated experimentally to be a high-sensitivity acoustic sensor with a large dynamic range over a wide frequency band. Optical contact technology was used to improve the robustness of the FPE, which consists of two parallel lenses with high reflectivity exceeding 99%. An acoustic signal detection system based on phase modulation spectrum technology was also constructed. A stable and high-Q value of 106 was measured for the FPE. As a result, high sensitivity of 177.6 mV/Pa was achieved. Because of the change in the refractive index of the air when it is modulated by the acoustic waves, a frequency response of 20 Hz–70 kHz with flatness of ±2 dB was obtained and a large dynamic range of 115.3 dB was measured simultaneously. The excellent performance of the device will be beneficial for optical acoustic sensing.
© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
As an alternative to conventional electro-acoustic sensors, fiber-optic acoustic sensors based on fused-tapered optical fiber couplers [1,2], Fabry-Pérot interferometers (FPIs) [3,4], fiber Bragg gratings (FBGs) [5,6] and other fiber devices [7], provide advantages including freedom from electromagnetic interference [8] and ease of miniaturization [9]. These sensors have been investigated widely for applications in industrial nondestructive testing [10], medical diagnosis [11–13], consumer electronics [14], and several other fields [15–17]. However, the mature fiber-optic acoustic sensors available at present mainly use moving parts such as membranes or optical fibers as their acoustic sensing units and simultaneous realization of both high sensitivity and a large dynamic range in combination with a broadband frequency response has thus proved challenging [18–20].
Another type of optical acoustic sensing technology has realized acoustic detection based on the modulation of light caused by the small changes in the refractive index of air induced by sound signals. In 2016, Balthasar Fischer of XARION Laser Acoustics used this principle to develop a fiber-optic acoustic sensor based on a Fabry-Pérot etalon (FPE), which is an interferometric cavity formed using two parallel semi-reflecting mirrors [21]. Although the broadband acoustic response of this type of sensor has been reported, it was difficult to attain high sensitivity and a large dynamic range because an FPE with a low quality factor (Q) and inferior finesse was used [22].
Here, we propose a transmissive micro-fiber-optic acoustic sensor based on the high-Q resonance effect of the FPE. In addition, the principle of use of direct coupling of light and the sound field for acoustic detection allows the sensor to remove the limitation of moving parts. This will enable broadband performance, high sensitivity and a large dynamic range to be achieved simultaneously. Manufactured using optical contact technology, an FPE with mirror reflectivity greater than 99% can have a high-Q-factor of the order of 106, according to the sharpness resonance spectrum, which will then realize strong optical confinement in the cavity. Furthermore, phase modulation spectroscopy technology is used for acoustic signal demodulation. The acoustic test results demonstrate that the sensor has flatness of ±2 dB in the 20 Hz–70 kHz frequency band. Excellent sensitivity of 177.6 mV/Pa and a large dynamic range of 115.3 dB are also realized. This work provides a significant concept to advance the development and application of fiber-optic acoustic sensors.
2. Detection principle and sensor fabrication
The proposed transmissive sensor is shown in Fig. 1(a) and consists of two fiber collimators and a high reflectivity FPE. When acoustic signals pass through the central opening of the rigid FPE, the sound pressure does not cause mechanical displacement of the cavity length; instead, it changes the molecular density of the air between the mirrors, which then causes a change in the air’s refractive index, as illustrated in Fig. 1(b). Using the formulas of JM Rüeger as a basis [23,24], it can be shown that there is a linear relationship between the change in the refractive index of air $\Delta n$ and the change in the sound pressure expressed as $\Delta p$, as shown in Eq. (1):
Fig. 1. Diagram of the acoustic detection method. (a) Acoustic signals passing through the transparent central opening of the transmissive FPE-based fiber-optic acoustic sensor; (b) the sound pressure causes change in the refractive index of the air between the FPE mirrors; (c) the correspondence relationship between the resonance frequency shift caused by the change in the refractive index of the air and the demodulation curve.
The sound pressure changes the refractive index of the air in the FPE, which induces a drift in the resonance frequency. This drift, denoted by $\Delta f$, is proportional to the sound pressure change $\Delta p$ and the relationship between these properties is
where k is the linear coefficient of the sound pressure change corresponding to the refractive index change, c is the speed of light in a vacuum, n is the refractive index of air, and d is the distance between the mirrors.Because the change in the refractive index of air caused by sound pressure is of the order of $\textrm{2}\textrm{.84} \times \textrm{1}{\textrm{0}^{\textrm{ - 9}}}\textrm{/Pa}$ that calculated by Eq. (1) (where $\lambda \textrm{ = 1}\textrm{.55}\mathrm{\mu }\textrm{m},$ $T = 273.15K,$ $\Delta p = 1\textrm{Pa}.$), the frequency difference generated by the resonance frequency shift of the high-Q FPE is very weak and is difficult to be measured directly. Phase modulation and lock-in amplification technique, i.e., phase modulation spectroscopy technology, are used for the detection of acoustic signals. The weak frequency difference signal with modulation signal is converted into electrical signal by photodetector and then input into lock-in amplifier. Based on the correlation detection principle, the weak frequency difference signal is amplified and extracted by the lock-in amplifier under the condition that the synchronization signal of the modulation signal is used as the reference signal. And at the same time, the noise and other interference signals with different frequencies and phases from the reference signal are filtered out. Thus, the signal to noise ratio of the acoustic sensing system can be improved to a great extent. Figure 1(c) shows the correspondence relationship between the resonance frequency shift and the demodulation curve, which allows the demodulation curve to be used as an error signal for feedback, thus controlling the laser frequency to track and lock the resonance frequency. After frequency locking, the acoustic response of the sensor can be obtained intuitively from the demodulation curve. A comparison of the characteristics before and after frequency locking and the sensor’s response to the acoustic signals are shown in Figs. 2(a) and 2(b), respectively.
Fig. 2. (a) Comparison of the signals before and after frequency locking; and (b) the sensor’s response to the acoustic signals.
To realize linear undistorted acoustic detection using the proposed sensor, the detectable resonance frequency offset must correspond to the linear working area of the demodulation curve. The change in the demodulation curve’s linear voltage for a given shift in the resonance frequency, and thus the sensitivity of the sensor, is dependent on the sharpness of the resonance. To achieve high sensitivity, the FPE structure is designed carefully. The rigid FPE is made entirely from glass, for which the surface figure is less than $\lambda \textrm{/20@632}\textrm{.8nm}$. The outer surfaces of the two flat plates have small wedge angles to avoid interference from reflected light on their surfaces. In addition, the outer surfaces S1 and S4 are coated with anti-reflection films with reflectivity of less than 0.2% and internal surfaces S2 and S3 are coated with highly reflective films with reflectivity exceeding 99%. The FPE manufacturing method uses optical contact technology, which enables small batch FPE production to be achieved with high consistency. A photograph of an FPE is shown in Fig. 3(a), where the FPE has dimensions of 6 mm × 6 mm, a thickness of 2 mm, and a transparent central opening with dimensions of 2 mm × 2 mm that is used to detect the acoustic waves. The resonance spectrum of the FPE, as shown in Fig. 3(b), is extremely sharp, which indicates that the FPE can achieve a very high degree of optical confinement. In addition, the quality factor of the FPE can reach up to the order of 106 and the corresponding finesse is approximately 387. This illustrates that the major advantage of the proposed sensor over the established low-reflectivity FPE acoustic sensors in current use is its high sensitivity and large dynamic range. Moreover, to enable practical application, the optical fiber collimators and the FPE are coupled and aligned to complete the packaging of the fiber-optic acoustic sensor, as shown in Fig. 4.
Fig. 3. (a) Photograph of the actual FPE; and (b) resonance spectrum of the FPE, where the full width at half maximum (FWHM) of the spectrum is 186.3 MHz, thus meaning that the quality factor of the FPE is$\textrm{1}\textrm{.04} \times \textrm{1}{\textrm{0}^\textrm{6}}$.
3. Experiment and discussion
Figure 5 illustrates the experimental setup used to characterize the acoustic performance of the sensor. In the standard whistle box, the inner walls are covered with acoustic damping materials to prevent the formation of acoustic standing waves, while the exterior walls are covered using gypsum sheets to dampen any noise from the laboratory. The proposed sensor and the calibrated reference sound level meter are placed symmetrically and are located equidistant to the loudspeaker in the standard whistle box. The loudspeaker (sound source) is driven by a power amplifier and the signal generator can produce acoustic signals ranging from 20 Hz to 100 kHz. To enable optical detection of the acoustic signals, a narrow linewidth laser with a central wavelength of 1550 nm that is connected to the phase modulator (PM) illuminates the sensor and a triangular wave signal is used to scan the laser. The transmitted light is received by the photodetector and the converted electric signal is demodulated using the lock-in amplifier. The demodulated signal is used as an error signal for feedback control of the laser frequency to achieve frequency locking through the lock-frequency controller (LFC). After frequency locking, the effect of the acoustic signal on the resonance frequency corresponds to the offset of the demodulation curve relative to zero, thus allowing intuitive acoustic detection to be realized.
Fig. 5. Layout of the experimental setup (PM: phase modulator; SG: signal generator; LIA: lock-in amplifier; PD: photodetector; OSC: oscilloscope; HVA: high voltage amplifier; LFC: lock-frequency controller; PA: power amplifier). The optical path is drawn in red and the electrical path is drawn in black.
Acoustic signals with constant amplitudes and frequencies in the range between 20 Hz and 100 kHz produced by the loudspeaker are applied to the sensor. Figure 6(a) shows the sensor frequency response over the range from 20 Hz to 70 kHz, which shows a flatness of ±2 dB. Also, the response of fiber-optic acoustic sensor to 1 kHz, 10 kHz, 20 kHz, and 40 kHz acoustic signals is shown in Fig. 6(b). Theoretically, the detection frequency range of the fiber-optic acoustic sensor is dependent on the beam diameter. When the frequency of the acoustic wave increases, the wavelength becomes shorter simultaneously. When the acoustic wavelength is close to the diameter of the laser beam, the maximum and minimum acoustic pressures will appear simultaneously inside the laser beam, causing the sensor to be unable to output an acoustic signal. The beam diameter of the fiber collimator is 300 µm, which means that the acoustic detection frequency of the sensor can theoretically reach 1.13 MHz. However, because of the restrictions of the current acoustic signal demodulation system, the sensor only responds to acoustic signals of up to 70 kHz. For example, the frequency bandwidth of the high-voltage amplifier that controls the laser scanning voltage and the response speed of the digital proportional-integral control module in the LFC are among the factors that will affect the demodulation of higher frequency acoustic signals. Improvements to the acoustic signal demodulation system in future work can broaden the measured frequency response bandwidth of the proposed sensor further.
Fig. 6. (a) Frequency response of the fiber-optic acoustic sensor; (b) response of fiber-optic acoustic sensor to 1 kHz, 10 kHz, 20 kHz, -40 kHz acoustic signals.
The acoustic pressure sensitivity is the ratio of the sensor’s output open circuit voltage to the free-field acoustic pressure at the sensor detection position. Acoustic signals at a fixed frequency (1 kHz) with varying intensity (from 0.28 Pa to 9.36 Pa) are generated. The outputs from the sound level meter and the sensor are collected separately and fitted linearly; the slope of the resulting plot is the sound pressure sensitivity of the sensor. Figure 7(a) shows the sensitivity fitting curve of the sensor at a modulation frequency of 4.6 MHz and with a modulation amplitude of 10 Vpp; the acoustic pressure sensitivity obtained is 177.6 mV/Pa, which is approximately one order of magnitude better than that of the low-reflectivity FPE-based fiber-optic acoustic sensor. The sensitivity can also be assessed using the minimum detectable sound pressure. Using the same modulation signal, the spectrum obtained for the minimum detectable acoustic signal is shown in Fig. 7(b). The signal-to-noise ratio is 12.7 dB and the resolution bandwidth is 18 Hz. Based on an input sound pressure of 0.0108 Pa, the minimum detectable sound pressure is calculated to be 0.53 $\textrm{mPa}/\sqrt {\textrm{Hz}}$. With reference to a sound pressure of 20 $\mathrm{\mu }\textrm{Pa}/\sqrt {\textrm{Hz}}$ in air, the minimum detectable sound pressure level is 29.40 dB.
Fig. 7. (a) Acoustic pressure sensitivity of the fiber-optic acoustic sensor; (b) response spectrogram of the sensor with respect to an acoustic signal of 10.8 mPa and 1 kHz.
The dynamic range of the fiber-optic acoustic sensor is determined by the minimum detectable sound pressure and the maximum detectable sound pressure. Because the sensor’s response to acoustic signals corresponds to the offset of the locked demodulation curve relative to the zero point, the maximum detectable sound pressure is dependent on the linear region of the demodulation curve. When the linear region of the demodulation curve has a large amplitude and a small slope, undistorted detection of high sound pressures can be achieved. In Fig. 8(a), the solid red line represents the sensitivity fitting curve of the sensor when the modulation frequency and the amplitude are 20 MHz and 10 Vpp, respectively; an expanded view of this curve is shown in Fig. 8(b). Because of the limitations of the loudspeaker’s power, the maximum sound pressure level that can be measured in the standard whistle box is only 114 dB, which does not exceed the linear amplitude of the demodulation curve. Then, based on the sensitivity fitting curve’s slope and the linear amplitude of the demodulation curve, as shown in inset 1, the maximum undistorted detectable sound pressure of the proposed sensor can be calculated theoretically to be 346.8 Pa, which is equivalent to a sound pressure level of 144.78 dB. Consequently, the dynamic range of the proposed sensor can be as high as 115.38 dB, which is better than the corresponding range of the existing fiber-optic acoustic sensors. Additionally, optimization of the sensor head and the acoustic demodulation system will enable acoustic detection over a wider range.
Fig. 8. (a)Theoretical maximum measureable sound pressure deduced from the slope and the linear amplitude of the demodulation curve, and (b) an expanded view of the sensitivity fitting curve of the sensor.
4. Conclusion
In summary, based on the high-Q resonance effect, we have demonstrated a transmissive micro-fiber-optic acoustic sensor using an FPE. Additionally, based on the sound detection principle that the sound pressure changes the refractive index of the air, which is used in combination with phase modulation spectroscopy technology, a broad band of 20 Hz–70 kHz with flatness of ±2 dB, excellent sensitivity of 177.6 mV/Pa and a large dynamic range of 115.3 dB are achieved simultaneously for the proposed sensor. This represents a major advance in fiber-optic acoustic sensor technology. The goals of our future work will be to make full use of the advantages and flexibility of the proposed design to achieve wider bandwidths, higher sensitivities and larger dynamic ranges for acoustic detection and to apply the proposed sensor to fields with a variety of different requirements.
Funding
The National Natural Science Foundation of China (61704160, 61771434); Shanxi “1331 Project” Key Subject Construction (1331KSC); the Natural Science Foundation of Shanxi Province (201801D221214); the Youth Academic Leader Support Program of North University of China (QX201804); and the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi; Shanxi Province Postgraduate Innovation Project (2020BY100).
Acknowledgments
The authors thank David MacDonald, MSc, from Liwen Bianji, Edanz Editing China (www.liwenbianji.cn/ac), for editing the English text of a draft of this manuscript.
Disclosures
The authors declare no conflicts of interest.
References
1. F. Li, Y. Liu, L. Wang, and Z. Zhao, “Investigation on the response of fused taper couplers to ultrasonic wave,” Appl. Opt. 54(23), 6986–6993 (2015). [CrossRef]
2. S. Ji, J. Tian, X. Dong, Y. Sun, and Y. Yao, “Multipoint All-Fiber Laser-Ultrasound Transducer Using Cascaded Fiber Waist-Enlarged Fusion Tapers,” J. Lightwave Technol. 36(16), 3284–3292 (2018). [CrossRef]
3. J. Wang, F. Ai, Q. Sun, T. Liu, H. Li, Z. Yan, and D. Liu, “Diaphragm-based optical fiber sensor array for multipoint acoustic detection,” Opt. Express 26(19), 25293–25304 (2018). [CrossRef]
4. Y. Wang, H. Yuan, X. Liu, Q. Bai, H. Zhang, Y. Gao, and B. Jin, “A Comprehensive Study of Optical Fiber Acoustic Sensing,” IEEE Access 7, 85821–85837 (2019). [CrossRef]
5. R. Gao, M. Zhang, and Z.-M. Qi, “Miniature all-fibre microflown directional acoustic sensor based on crossed self-heated micro-Co2+-doped optical fibre Bragg gratings,” Appl. Phys. Lett. 113(13), 134102 (2018). [CrossRef]
6. G. Liang, J. Jiang, K. Liu, W. Shuang, T. Xu, W. Chen, Z. Ma, Z. Ding, X. Zhang, Z. Yongning, and T. Liu, “Phase Demodulation Method Based on Dual-Identical-Chirped-Pulse and Weak Fiber Bragg Gratings for Distributed Acoustic Sensing,” Photonics Res. 8(7), 1093–1099 (2020). [CrossRef]
7. T. Jiang, Q. He, and Z.-K. Peng, “Enhanced directional acoustic sensing with phononic crystal cavity resonance,” Appl. Phys. Lett. 112(26), 261902 (2018). [CrossRef]
8. P. Fan, W. Yan, P. Lu, W. Zhang, W. Zhang, F. Xin, and J. Zhang, “High Sensitivity Fiber-Optic Michelson Interferometric Low-Frequency Acoustic Sensor Based on Gold Diaphragm,” Opt. Express 28(17), 25238–25249 (2020). [CrossRef]
9. X. Fu, P. Lu, J. Zhang, Z. Qu, W. Zhang, Y. Li, P. Hu, W. Yan, W. Ni, D. Liu, and J. Zhang, “Micromachined extrinsic Fabry-Pérot cavity for low-frequency acoustic wave sensing,” Opt. Express 27(17), 24300–24310 (2019). [CrossRef]
10. L. Shiloh, A. Lellouch, R. Giryes, and A. Eyal, “Fiber-optic distributed seismic sensing data generator and its application for training classification nets,” Opt. Lett. 45(7), 1834–1837 (2020). [CrossRef]
11. Z. Guo, G. Li, and S.-L. Chen, “Miniature probe for all-optical double gradient-index lenses photoacoustic microscopy,” J. Biophotonics 11(12), e201800147 (2018). [CrossRef]
12. J. Bauer-Marschallinger, A. Höllinger, B. Jakoby, P. Burgholzer, and T. Berer, “Fiber-optic annular detector array for large depth of field photoacoustic macroscopy,” Photoacoustics 5, 1–9 (2017). [CrossRef]
13. Y. Liu, Y. Shen, C. Ma, J. Shi, and L. V. Wang, “Lock-in camera based heterodyne holography for ultrasound-modulated optical tomography inside dynamic scattering media,” Appl. Phys. Lett. 108(23), 231106 (2016). [CrossRef]
14. S. E. Hayber, T. E. Tabaru, S. Keser, and O. G. Saracoglu, “A Simple, High Sensitive Fiber Optic Microphone Based on Cellulose Triacetate Diaphragm,” J. Lightwave Technol. 36(23), 5650–5655 (2018). [CrossRef]
15. F. Yu and Y. Okabe, “Fiber-Optic Sensor-Based Remote Acoustic Emission Measurement in a 1000 °C Environment,” Sensors 17(12), 2908 (2017). [CrossRef]
16. Z. Luo, Y. Yang, Z. Wang, M. Yu, C. Wu, T. Chang, P. Wu, and H.-L. Cui, “Low-frequency fiber optic hydrophone based on weak value amplification,” Opt. Express 28(18), 25935–25948 (2020). [CrossRef]
17. H. Liu, J. Ma, W. Yan, W. Liu, X. Zhang, and C. Li, “Traffic Flow Detection Using Distributed Fiber Optic Acoustic Sensing,” IEEE Access 6, 68968–68980 (2018). [CrossRef]
18. Y. Wu, C. Yu, F. Wu, C. Li, J. Zhou, Y. Gong, Y. Rao, and Y. Chen, “A Highly Sensitive Fiber-Optic Microphone Based on Graphene Oxide Membrane,” J. Lightwave Technol. 35(19), 4344–4349 (2017). [CrossRef]
19. B. Liu, H. Zhou, L. Liu, X. Wang, M. Shan, P. Jin, and Z. Zhong, “An Optical Fiber Fabry-Perot Microphone Based on Corrugated Silver Diaphragm,” IEEE Trans. Instrum. Meas. 67(8), 1994–2000 (2018). [CrossRef]
20. C. Li, X. Peng, H. Zhang, C. Wang, S. Fan, and S. Cao, “A sensitivity-enhanced flexible acoustic sensor using side-polished fiber Bragg grating,” Measurement 117, 252–257 (2018). [CrossRef]
21. B. Fischer, “Optical microphone hears ultrasound,” Nat. Photonics 10(6), 356–358 (2016). [CrossRef]
22. S. Preisser, W. Rohringer, M. Liu, C. Kollmann, S. Zotter, B. Fischer, and W. Drexler, “All-optical highly sensitive akinetic sensor for ultrasound detection and photoacoustic imaging,” Biomed. Opt. Express 7(10), 4171–4186 (2016). [CrossRef]
23. D. D. Wijaya and F. K. Brunner, “Atmospheric range correction for two-frequency SLR measurements,” J. Geod. 85(9), 623–635 (2011). [CrossRef]
24. A. Hofmeister and J. Böhm, “Application of ray-traced tropospheric slant delays to geodetic VLBI analysis,” J. Geod. 91(8), 945–964 (2017). [CrossRef]
