Detection Of Acoustic Waves Research Articles

Rapid point-of-care breath test predicts breast cancer and abnormal mammograms in symptomatic women

Previous studies have reported volatile organic compounds (VOCs) in the breath as biomarkers of breast cancer. These biomarkers may be derived from cancer-associated fibroblasts, in which oxidative stress degrades polyunsaturated fatty acids to volatile alkanes and methylated alkane derivatives that are excreted in the breath. We evaluated a rapid point-of-care test for breath VOC biomarkers as predictors of breast cancer and abnormal mammograms.&#xD;Methods: We studied 593 women aged ≥ 18 yr referred to three sites for mammography for a symptomatic breast-related concern (e.g. breast mass, nipple discharge). A rapid point-of-care breath testing system collected and concentrated alveolar breath VOCs on a sorbent trap and analyzed them with gas chromatography and surface acoustic wave detection in < 6 min. Breath VOC chromatograms were randomly assigned to a training set or to a validation set. Monte Carlo analysis identified significant breath VOC biomarkers of breast cancer and abnormal mammograms in the training set, and these biomarkers were incorporated into a multivariate algorithm to predict disease in the validation set. &#xD;Results: Prediction of breast cancer: 50 women had biopsy-proven breast cancer (invasive cancer 41, ductal non-invasive cancer 9)&#xD;Unsplit data set: Breath VOCs identified breast cancer with 83% accuracy (area under curve of receiver operating characteristic), 82% sensitivity and 77.1% specificity.&#xD;Split data sets: Training set breath VOCs identified breast cancer with 80.3% accuracy, 84% sensitivity and 74.3% specificity. Corresponding values in the validation set were 68%% accuracy, 72.4% sensitivity and 61.5% specificity.&#xD;Prediction of BIRADS 4 and 5 mammograms (versus BIRADS 1, 2 and 3): &#xD;Unsplit data set: Breath VOCs identified abnormal mammograms with 76.2% accuracy.&#xD;Split data sets: Breath VOCs identified abnormal mammograms with 74.2% accuracy, 73.3% sensitivity and 60% specificity. Corresponding values in the validation set were 60.5% accuracy, 64.2% sensitivity and 51% specificity.&#xD;Conclusions: A rapid point-of-care test for breath VOC biomarkers predicted risk of breast cancer and abnormal mammograms in women with breast-related symptoms.&#xD;&#xD.

High-resolution optical fiber underwater acoustic sensor enhanced by PDMS coating

This study introduces a high-resolution optical fiber underwater acoustic sensor utilizing a Fabry-Perot (FP) interferometer design. The sensor consists of a single-mode fiber (SMF) integrated with polydimethylsiloxane (PDMS), forming an FP cavity at the coated SMF terminus. The exceptional elasticity of PDMS amplifies vibrations from acoustic stimuli, modulating the FP cavity for effective acoustic wave detection. This integration of the probe within a single fiber, along with the PDMS coating technique, enhances the sensor’s SNR, resolution, and frequency response. The sensor’s simplicity, cost-effectiveness, superior signal-to-noise ratio, and low power consumption make it a promising tool for underwater acoustic applications.

Preparation of Fibrous Three-Dimensional Porous Materials and Their Research Progress in the Field of Stealth Protection.

Intelligent and diversified development of modern detection technology greatly affects the battlefield survivability of military targets, especially infrared, acoustic wave, and radar detection expose targets by capturing their unavoidable infrared radiation, acoustic wave, and electromagnetic wave information, greatly affecting their battlefield survival and penetration capabilities. Therefore, there is an urgent need to develop stealth-protective materials that can suppress infrared radiation, reduce acoustic characteristics, and weaken electromagnetic signals. Fibrous three-dimensional porous materials, with their high porosity, excellent structural adjustability, and superior mechanical properties, possess strong potential for development in the field of stealth protection. This article introduced and reviewed the characteristics and development process of fibrous three-dimensional porous materials at both the micrometer and nanometer scales. Then, the process and characteristics of preparing fibrous three-dimensional porous materials through vacuum forming, gel solidification, freeze-casting, and impregnation stacking methods were analyzed and discussed. Meanwhile, their current application status in infrared, acoustic wave, and radar stealth fields was summarized and their existing problems and development trends in these areas from the perspectives of preparation processes and applicability were analyzed. Finally, several prospects for the current challenges faced by fibrous three-dimensional porous materials were proposed as follows: functionally modifying fibers to enhance their applicability through self-cross-linking; establishing theoretical models for the transmission of thermal energy, acoustic waves, and electromagnetic waves within fibrous porous materials; constructing fibrous porous materials resistant to impact, shear, and fracture to meet the needs of practical applications; developing multifunctional stealth fibrous porous materials to confer full-spectrum broadband stealth capability; and exploring the relationship between material size and mechanical properties as a basis for preparing large-scale samples that meet the application's requirement. This review is very timely and aims to focus researchers' attention on the importance and research progress of fibrous porous materials in the field of stealth protection, so as to solve the problems and challenges of fibrous porous materials in the field of stealth protection and to promote the further innovation of fibrous porous materials in terms of structure and function.

Local Detection of Ground Coupled Acoustic Waves with Seismic Arrays and Their Potential Role in the Discrimination of Explosions and Earthquakes

Abstract Acoustic waves are widely used to characterize explosive sources such as volcanoes, meteorites, and controlled explosions. This study examines the potential role of ground coupled airwaves (GCA), which effectively propagate at acoustic speeds (∼0.34 km/s) before coupling to the ground near seismometers, in aiding local discrimination between low-yield explosions in shallow boreholes and earthquakes. GCA generated by shallow borehole explosions from the 2014 imaging magma under St. Helens experiment (ML 0.9–2.3) and earthquakes (ML 2–3.4) from 2014 to 2016, were recorded by various seismometers at &amp;lt;150 km source–receiver distance. Potential GCA are analyzed using arrays of broadband seismometers (number of seismometers, n = 85), nodal seismometers with 10-Hz geophones atop the surface (n = 904), and Texan dataloggers with shallowly buried 4.5-Hz geophones (n = 2535). Array-based detections are defined using the distributions of short-time average over long-time average functions in time windows during and adjacent to the predicted GCA arrival for direct source–receiver transmission. GCA are detected for 14 of 23 borehole explosions and 0 of 34 earthquakes. All detections occurred during times of low-mean wind speed (&amp;lt;0.5 m/s) at ground-based weather stations. GCA amplitudes exhibit strong spatial variability, and the number of spatially distributed receivers appears more important for GCA detection than the type of seismometer installation. GCA detections were compared with seismic P/S amplitude ratios, which are a common source discriminant, and field logs of whether the borehole explosions ejected any mass or deformed the surface. No clear correlation was found with either type of source information, suggesting that heterogeneous propagation and near-receiver effects like wind noise are more influential than variations in source processes among the 23 explosions. Our results indicate that local seismic detection of GCA may valuably complement discrimination metrics like P/S ratios, with a low tendency for false-positive indications of explosions but a high tendency for false negatives.

Regression Method for Rail Fastener Tightness Based on Center-Line Projection Distance Feature and Neural Network

In the railway system, fasteners have the functions of damping, maintaining the track distance, and adjusting the track level. Therefore, routine maintenance and inspection of fasteners are important to ensure the safe operation of track lines. Currently, assessment methods for fastener tightness include manual observation, acoustic wave detection, and image detection. There are limitations such as low accuracy and efficiency, easy interference and misjudgment, and a lack of accurate, stable, and fast detection methods. Aiming at the small deformation characteristics and large elastic change of fasteners from full loosening to full tightening, this study proposes high-precision surface-structured light technology for fastener detection and fastener deformation feature extraction based on the center-line projection distance and a fastener tightness regression method based on neural networks. First, the method uses a 3D camera to obtain a fastener point cloud and then segments the elastic rod area based on the iterative closest point algorithm registration. Principal component analysis is used to calculate the normal vector of the segmented elastic rod surface and extract the point on the centerline of the elastic rod. The point is projected onto the upper surface of the bolt to calculate the projection distance. Subsequently, the mapping relationship between the projection distance sequence and fastener tightness is established, and the influence of each parameter on the fastener tightness prediction is analyzed. Finally, by setting up a fastener detection scene in the track experimental base, collecting data, and completing the algorithm verification, the results showed that the deviation between the fastener tightness regression value obtained after the algorithm processing and the actual measured value RMSE was 0.2196 mm, which significantly improved the effect compared with other tightness detection methods, and realized an effective fastener tightness regression.

Underwater Low-Frequency Acoustic Wave Detection Based on a High-Q CaF2 Resonator

Whispering gallery mode (WGM) resonators with an ultra-high quality (Q) factor provide a new idea for high-precision underwater acoustic sensing. However, acoustic energy loss due to watertight encapsulation has become an urgent problem for its underwater application. In order to solve this problem, this paper proposes a hollowed-out array structure. The finite element simulation shows that the acoustic wave transmission loss is improved by 30 dB compared with that of the flat plate encapsulation structure. Using a calcium fluoride (CaF2) resonator with a Q factor of 1.2 × 108 as an acoustic sensitive unit, the amplitude and frequency of the loaded acoustic wave are retrieved by means of the dispersion coupling response mechanism. The resonator’s underwater experimental test range is 100 Hz–1 kHz, its acoustic sensing sensitivity level reaches −176.3 dB re 1 V/µPa @ 300 Hz, and its minimum detectable pressure can be up to 0.87 mPa/Hz1/2, which corresponds to a noise-equivalent pressure (NEP) of up to 58 dB re 1 µPa/Hz1/2.

Stretchable, stable, and structural color reversible enabled by mesoscopic regulation and design for flexible photonic crystal mechanical sensors

This paper reports a flexible mechanical sensor developed by combining an opal photonic crystal and a flexible medium through UV curing technology. Under the action of external force, the deformation of the flexible medium causes the change of the photonic crystal lattice constant, which leads to the displacement of the reflection peaks, thus realizing the detection of the deformation of the film. The flexible medium is mixed by photoinitiators and polymer monomers, and its mechanical properties are directly related to the mass fraction of photoinitiators and polymer monomers. The results show that the film can reach a maximum strain of about 180% when the mass fraction of photoinitiator is 3% and the volume ratio of the polymer functional monomers is 8:2. In addition, for the responsiveness test of the sensor under tensile, the results show that at 0%, 26%, and 78% of tensile strain, its structural color is blue-shifted sequentially, and its spectral peaks are 668 nm, 535 nm, and 488 nm, respectively. Finally, the sensor is applied to the detection of acoustic waves in air, and it is found that its spectral response peaks can be obtained for acoustic waves of different frequencies (250–650 Hz), and a spectral peak at 500 Hz. This flexible photon sensor has the potential to match the acoustic resistance of water. It will greatly expand the response research of ocean exploration in the low frequency range.

Detection of Water Surface Acoustic Waves Using Sinusoidal Phase Modulation Interferometer and Prenormalized PGC-Arctan Algorithm

A sinusoidal phase modulation laser interferometer is proposed to detect water surface acoustic waves excited by underwater acoustic radiation, and an improved PGC-Arctan demodulation algorithm that combines prenormalization and Lissajous ellipse fitting is proposed to demodulate detection signals. In this paper, the effects of phase modulation depth, carrier phase delay, and interference signal visibility on the Lissajous figure formed by quadrature interference components are analyzed. The demodulation algorithm first uses the amplitudes of multiple Fourier spectral components of an interference signal to calculate the phase modulation depth C, and calculation of the carrier phase delay Vc is achieved through the introduction of a quadrature carrier signal. Then, certain coefficients regarding C and Vc are constructed for prenormalization of the two quadrature interference signal components to eliminate the local nonuniform widening phenomenon of Lissajous ellipse. Next, the outer and the inner contours are extracted from a uniformly widened Lissajous ellipse resulting from light intensity disturbance, and the axial ratio of the ellipse is obtained, which is used to correct the ratio of the quadrature interference signal to eliminate the effect of filter gain coefficients. At last, through the combination of an Arctan algorithm and a phase-unwrapping algorithm, high-precision demodulation of the interference signal is realized. A sinusoidal phase modulation interferometer was set up to detect water surface acoustic waves, and a series of detection experiments were carried out. The experiment results show that the detection method and demodulation algorithm described in this paper can accurately realize the measurement of weak water surface acoustic waves. The proposed algorithm shows less distortion in demodulation results, and its signal-to-noise distortion ratio is less than 20 dB at 500 Hz, which is significantly better than traditional algorithms. The experimental results demonstrate the effectiveness and accuracy of water surface acoustic wave detection using sinusoidal phase modulation interferometer.

Coherently parallel fiber-optic distributed acoustic sensing using dual Kerr soliton microcombs.

Fiber-optic distributed acoustic sensing (DAS) has proven to be a revolutionary technology for the detection of seismic and acoustic waves with ultralarge scale and ultrahigh sensitivity, and is widely used in oil/gas industry and intrusion monitoring. Nowadays, the single-frequency laser source in DAS becomes one of the bottlenecks limiting its advance. Here, we report a dual-comb-based coherently parallel DAS concept, enabling linear superposition of sensing signals scaling with the comb-line number to result in unprecedented sensitivity enhancement, straightforward fading suppression, and high-power Brillouin-free transmission that can extend the detection distance considerably. Leveraging 10-line comb pairs, a world-class detection limit of 560 fε/√Hz@1 kHz with 5 m spatial resolution is achieved. Such a combination of dual-comb metrology and DAS technology may open an era of extremely sensitive DAS at the fε/√Hz level, leading to the creation of next-generation distributed geophones and sonars.

Ionospheric response to the 2020 Samos earthquake and tsunami

On 30 October 2020 at 11:51 UT, a magnitude 7.0 earthquake occurred in the Dodecanese sea (37.84°N, 26.81°E, 10 km depth) and generated a tsunami with an observed run-up of more than 1 m on the Turkish coasts. Both the earthquake and the tsunami produced acoustic and gravity waves that propagated upward, triggering co-seismic and co-tsunamic ionospheric disturbances. This paper presents a multi-instrumental study of the ionospheric impact of the earthquake and related tsunami based on ionosonde data, ground-based Global Navigation Satellite Systems (GNSS) data and data from DORIS beacons received by Jason3 in the Mediterranean region. Our study focuses on the Total Electron Content to describe the propagation of co-seismic and co-tsunami ionospheric disturbances (CSID, CTID), possibly related to gravity waves triggered by the earthquake and tsunami. We use simultaneous vertical ionosonde soundings to study the interactions between the upper and lower atmosphere, highlighting the detection of acoustic waves generated by the seismic Rayleigh waves reaching the ionosonde locations and propagating vertically up to the ionosphere. The results of this study provide a detailed picture of the Lithosphere-Atmosphere–Ionosphere coupling in the scarcely investigated Mediterranean region and for a relatively weak earthquake.Graphical abstract

Graphene-based Two-Stage Enhancement Pressure Sensor for Subtle Mechanical Force Monitoring.

The development of pressure sensors with high sensitivity and a low detection limit for subtle mechanical force monitoring and the understanding of the sensing mechanism behind subtle mechanical force monitoring are of great significance for intelligent technology. Here, we proposed a graphene-based two-stage enhancement pressure sensor (GTEPS), and we analyzed the difference between subtle mechanical force monitoring and conventional mechanical force monitoring. The GTEPS exhibited a high sensitivity of 62.2 kPa-1 and a low detection limit of 0.1 Pa. Leveraging its excellent performance, the GTEPS was successfully applied in various subtle mechanical force monitoring applications, including acoustic wave detection, voice-print recognition, and pulse wave monitoring. In acoustic wave detection, the GTEPS achieved a 100% recognition accuracy for six words. In voiceprint recognition, the sensor exhibited accurate identification of distinct voiceprints among individuals. Furthermore, in pulse wave monitoring, GTEPS demonstrated effective detection of pulse waves. By combination of the pulse wave signals with electrocardiogram (ECG) signals, it enabled the assessment of blood pressure. These results demonstrate the excellent performance of GTEPS and highlight its great potential for subtle mechanical force monitoring and its various applications. The current results indicate that GTEPS shows great potential for applications in subtle mechanical force monitoring.

Outstanding Synergy of Sensitivity and Linear Range Enabled by Multigradient Architectures.

Flexible pressure sensors are devices that mimic the sensory capabilities of natural human skin and enable robots to perceive external stimuli. One of the main challenges is maintaining high sensitivity over a broad linear pressure range due to poor structural compressibility. Here, we report a flexible pressure sensor with an ultrahigh sensitivity of 153.3 kPa-1 and linear response over an unprecedentedly broad pressure range from 0.0005 to 1300 kPa based on interdigital-shaped, multigradient architectures, featuring modulus, conductivity, and microstructure gradients. Such multigradient architectures and interdigital-shaped configurations enable effective stress transfer and conductivity regulation, evading the pressure sensitivity-linear range trade-off dilemma. Together with high pressure resolution, high frequency response, and good reproducibility over the ultrabroad linear range, proof-of-concept applications such as acoustic wave detection, high-resolution pressure measurement, and healthcare monitoring in diverse scenarios are demonstrated.

Guided acoustic waves in thin epitaxial films: Experiment and inverse problem solution for NiTi

Despite the fundamental and technological importance of the elastic constants, a suitable method for their full characterization in epitaxial films is missing. Here we show that transient grating spectroscopy (TGS) with highly k-vector-selective generation and detection of acoustic waves is capable of determination of all independent elastic coefficients of an epitaxial thin film grown on a single-crystalline substrate. This experimental setup enables detection of various types of guided acoustic waves and evaluation of the directional dependence of their speeds of propagation. For the studied model system, which is a 3μm thin epitaxial film of the NiTi shape memory alloy on an MgO substrate, the TGS angular maps include Rayleigh-type surface acoustic waves as well as Sezawa-type and Love-type modes, delivering rich information on the elastic response of the film under different straining modes. The resulting inverse problem, which means the calculation of the elastic constants from the TGS maps, is subsequently solved using the Ritz–Rayleigh numerical method. Using this approach, tetragonal elastic constants of the NiTi film and their changes with the austenite→martensite phase transition are analyzed.

Optical generation and detection of GHz longitudinal and transverse acoustic waves in solids assisted by two-dimensional metallic grating structure

Absorption of laser pulses with picosecond temporal width in a two-dimensional nano-scale metallic grating deposited on a transparent substrate launches both longitudinal and transverse acoustic waves in to the sample. The periodic metallic structure makes the generated acoustic waves propagate several different directions. The propagating acoustic waves are monitored optically by the delayed light pulses (probe light) as the transient reflectivity change which is known as the Brillouin oscillation. The probe light is also diffracted by the metallic grating, allowing the detection of the acoustic waves propagating in the multiple directions efficiently. The analysis of the Brillouin oscillation frequencies brings the longitudinal and transverse sound velocities and the optical refractive index simultaneously from a single measurement. We verify the above mentioned scheme using a sample with two-dimensional square lattice (period 380 nm) of aluminum square islands of lateral dimension 200 × 200 nm2 and thickness of 50 nm on a fused silica substrate of thickness 1 mm. From the obtained Brillouin oscillation frequencies in several tens GHz, the acoustic and optical properties of the substrate material are successfully retrieved. The technique would be applicable to investigate the acoustic and optical properties of more complicated systems, such as anisotropic and/or inhomogeneous medium.

3D printed Fabry-Perot acoustic probe with a glass horn tube

Sensing an incoming acoustic signal is typically associated with absorbing the energy, perturbing the measurement and therefore causing a deformation of the sensing elements, which is mainly related to the acoustic wave pressure. Here, we demonstrated a fiber-tip based Fabry-Perot (FP) acoustic probe sensor, which was directly printed on an optical fiber tip by a two-photon 3D printing technique and assembled by a glass horn structure, which can improve the sensitivity. It showed that the sensor has a −3 dB bandwidth of 366.05 kHz at the first resonant frequency of 467.84 kHz. A low noise-limited minimum detectable pressure level of 4.71 mPa/Hz1/2@100 kHz is obtained. Due to the acoustic wave focusing property of the horn structure, the detected signal intensity can be amplified by 4 times as the sensor located at the bottom position. It demonstrates that 3D printed micro acoustic devices could be used for weak acoustic wave detection in the applications of partial discharge, photoacoustic imaging and non-destructive detection.

Water Surface Acoustic Wave Detection by a Millimeter Wave Radar

Feature extraction and recognition of underwater targets are important in military and civilian areas. This paper studied water surface acoustic wave (WSAW) detection by a millimeter wave (mmWave) radar. The mmWave-based endpoint detection method of the WSAW was introduced. Simulated results show that the continuous wavelet transform (CWT) method has a better detection performance. A 77 GHz large aperture antenna mmWave radar sensor and an underwater acoustic transmitter have been applied to conduct laboratory experiments. Still water surface experimental results verify that the CWT method has better detection capability, and the mmWave radar can accurately detect even 155 nm WSAW. Wavy water surface experimental results demonstrate the ability of the mmWave radar to analyze the time-frequency feature of the weak WSAW signal. These works indicate the potential of mmWave radar for the cross-medium detection and recognition of underwater targets.

Initial exploration on potential fire hazards detection from coal spontaneous combustion applied by acoustic wave

Coal spontaneous combustion often wastes resources and causes environmental pollution. Rapid and accurate identification of high temperature areas in coal is essential to reducing such combustion and environmental pollution. The acoustic thermometry method has the benefits of large temperature measurement space, non-contact, and high interference resistance. Determining the attenuation characteristics of acoustic waves in loose coal is the basis and premise for realizing acoustic temperature measurement. Four types of bituminous coal were scanned by computer tomography equipment. A self-designed acoustic attenuation test device was used to test coal samples under different temperatures and particle sizes. The study result demonstrates that the distribution characteristics of loose coal voids are mainly related to the particle size. The smaller the particle size range, the more uniform the void distribution. As the size of the coal particles increases, the voids become larger. The acoustic attenuation coefficients of four coal samples showed an increasing trend as frequency increased. The influence of coal particle size distribution on the acoustic attenuation coefficient was greater than that of temperature and metamorphic degree. The peak values of coal sound attenuation for different particle sizes were around 400, 700, 1100, and 1600 Hz. This indicated that the distribution of voids was the main factor affecting the propagation of acoustic waves. By analysing the attenuation mechanism of the acoustic wave in loose coal, the attenuation of acoustic temperature measurement signal was caused by the combined effect of loose coal on acoustic wave absorption and scattering. The study results provide theoretical support for the realization of acoustic wave detection of high temperature point in loose coal spontaneous combustion.

Advanced Image Post-Processing Methods for Photoacoustic Tomography: A Review

Photoacoustic tomography (PAT) is a promising imaging technique that utilizes the detection of light-induced acoustic waves for both morphological and functional biomedical imaging. However, producing high-quality images using PAT is still challenging and requires further research. Besides improving image reconstruction, which turns the raw photoacoustic signal into a PAT image, an alternative way to address this issue is through image post-processing, which can enhance and optimize the reconstructed PAT image. Image post-processing methods have rapidly emerged in PAT and are proven to be essential in improving image quality in recent research. In this review, we investigate the need for image post-processing in PAT imaging. We conduct a thorough literature review on the latest PAT image post-processing articles, including both general and PAT-specific post-processing techniques. In contrast to previous reviews, our analysis focuses specifically on advanced image post-processing rather than image reconstruction methods. By highlighting their potential applications, we hope to encourage further research and development in PAT image post-processing technology.

Two-photon 3D printed spring-based Fabry–Pérot cavity resonator for acoustic wave detection and imaging

Optical fiber microresonators have attracted considerable interest for acoustic detection because of their compact size and high optical quality. Here, we have proposed, designed, and fabricated a spring-based Fabry–Pérot cavity microresonator for highly sensitive acoustic detection. We observed two resonator vibration modes: one relating to the spring vibration state and the other determined by the point-clamped circular plate vibration mode. We found that the vibration modes can be coupled and optimized by changing the structure size. The proposed resonator is directly 3D printed on an optical fiber tip through two-photon polymerization and is used for acoustic detection and imaging. The experiments show that the device exhibits a high sensitivity and low noise equivalent acoustic signal level of 2.39 mPa/Hz1/2 at 75 kHz that can detect weak acoustic waves, which can be used for underwater object imaging. The results demonstrate that the proposed work has great potential in acoustic detection and biomedical imaging applications.

PVDF Membrane-Based Dual-Channel Acoustic Sensor Integrating the Fabry–Pérot and Piezoelectric Effects

A resonant acoustic wave detector combined with Fabry-Pérot interference (FPI) and piezoelectric (PE) effects based on a polyvinylidene fluoride (PVDF) piezoelectric film was proposed to enhance the ability of the sensor to detect acoustic signals in a specific frequency band. The deformation of circular thin films was indicated by the interference and piezoelectric effects simultaneously, and the noise level was decreased by the real-time convolution of the two-way parallel signal. This study reveals that, at the film's resonance frequency, the minimum detection limits for the FPI and piezoelectric impacts on acoustic waves are 3.39 μPa/Hz1/2 and 20.8 μPa/Hz1/2, respectively. The convolution result shows that the background noise was reduced by 98.81% concerning the piezoelectric signal, and by 85.21% concerning the FPI signal. The convolution's signal-to-noise ratio (SNR) was several times greater than the other two signals at 10 mPa. Therefore, this resonance sensor, which the FPI and the piezoelectric effect synergistically enhance, can be applied to scenarios of acoustic wave detection in a specific frequency band and with ultrahigh sensitivity requirements.