Sound Field Imaging Research Articles

Diffusion-model-based inverse problem processing for optically-measured sound field

This paper proposes a diffusion-model-based method for addressing inverse problems in optical sound-field imaging. Optical sound-field imaging, known for its high spatial resolution, measures sound by detecting small variations in the refractive index of air caused by sound but often suffers from unavoidable noise contamination. Therefore, we present a diffusion model-based approach for sound-field inverse problems, including denoising, noisy sound-field reconstruction and extrapolation. During inference, sound-field degradation is introduced into the inverse denoising process, with range-null space decomposition used as a solver to handle degradation, iteratively generating degraded sound-field information. Numerical experiments show that our method outperforms other deep-learning-based methods in denoising and reconstruction tasks, and obtains effective results in extrapolation task. The experimental results demonstrate the applicability of our model to the real world.

An acoustic imaging recognition based cutting tools wear state prediction method

Online monitoring of cutting tools wear is an important component of advanced manufacturing technology, which can greatly improve the processing efficiency and reduce the production cost. In this paper, a cutting tools wear state prediction method based on acoustic imaging recognition is developed. By applying the advantages of the functional generalized inverse beamforming method in the sound field reconstruction, the acoustic signal is used as the carrier to reconstruct the three-dimensional space radiated sound field. And then, slice the reconstructed sound field image and input it into the convolutional neural network model as a sample, to process and classify the image and mines the feature information related to state from the sound field image. By incorporating amplitude and phase information of the sound field, the presented method utilizes spatial domain mapping to accurately identify the noise source and address challenges such as low recognition rate and difficult diagnosis under weak fault conditions. Furthermore, the paper also demonstrates the recognition of sound field states through a fault experiment in sound box simulation, based on these theories. And the recognition of sound field states is achieved through a simulation fault experiment conducted on the sound box, thereby validating the feasibility of the state monitoring method based on pattern recognition of sound and image. Finally, the experimental object is selected as the four-edge carbide milling cutter, and the cutting tools wear state is monitored by integrating sound field reconstruction techniques with convolution feature extraction methods to validate the robustness of the proposed approach.

Sound-field image denoising using deep neural network considering physical characteristics of sound

This paper presents a method of denoising utilizing deep neural networks (DNN) in sound field images measured by optical methods. Optical sound measurement has attracted much attention because of its capability to visualize sound field with high spatial resolution from a distance, which is difficult with conventional microphones. However, optical methods have the issue of the measured sound-field images often being heavily distorted by noise. This is caused by the weak phase of light changed by sound. Conventionally, noise-reduction filters considering the physical properties of sound have been known to be used for sound-field denoising. In this background, we propose a DNN-based sound-field denoising method that takes into account the physical properties of sound. In the DNN, a network architecture originally used for denoising natural images is employed, and we integrate loss functions based on the Helmholtz equation. Additionally, a 2D sound field dataset obtained from numerical acoustic simulation with random parameters is used during the training. Numerical and experimental data comparison experiments showed that the proposed DNN-based sound-field denoising outperformed the previous non-DNN methods.

On the imaging depth limit of photoacoustic tomography in the visible and first near-infrared windows.

It is well known that photoacoustic tomography (PAT) can circumvent the photon scattering problem in optical imaging and achieve high-contrast and high-resolution imaging at centimeter depths. However, after two decades of development, the long-standing question of the imaging depth limit of PAT in biological tissues remains unclear. Here we propose a numerical framework for evaluating the imaging depth limit of PAT in the visible and the first near-infrared windows. The established framework simulates the physical process of PAT and consists of seven modules, including tissue modelling, photon transportation, photon to ultrasound conversion, sound field propagation, signal reception, image reconstruction, and imaging depth evaluation. The framework can simulate the imaging depth limits in general tissues, such as the human breast, the human abdomen-liver tissues, and the rodent whole body and provide accurate evaluation results. The study elucidates the fundamental imaging depth limit of PAT in biological tissues and can provide useful guidance for practical experiments.

Deep sound-field denoiser: optically-measured sound-field denoising using deep neural network.

This paper proposes a deep sound-field denoiser, a deep neural network (DNN) based denoising of optically measured sound-field images. Sound-field imaging using optical methods has gained considerable attention due to its ability to achieve high-spatial-resolution imaging of acoustic phenomena that conventional acoustic sensors cannot accomplish. However, the optically measured sound-field images are often heavily contaminated by noise because of the low sensitivity of optical interferometric measurements to airborne sound. Here, we propose a DNN-based sound-field denoising method. Time-varying sound-field image sequences are decomposed into harmonic complex-amplitude images by using a time-directional Fourier transform. The complex images are converted into two-channel images consisting of real and imaginary parts and denoised by a nonlinear-activation-free network. The network is trained on a sound-field dataset obtained from numerical acoustic simulations with randomized parameters. We compared the method with conventional ones, such as image filters, a spatiotemporal filter, and other DNN architectures, on numerical and experimental data. The experimental data were measured by parallel phase-shifting interferometry and holographic speckle interferometry. The proposed deep sound-field denoiser significantly outperformed the conventional methods on both the numerical and experimental data. Code is available on GitHub (https://github.com/nttcslab/deep-sound-field-denoiser).

Speckle holographic imaging of a sound field using Fresnel lenses.

In this Letter, we propose to use Fresnel lenses for holographic sound-field imaging. Although a Fresnel lens has never been used for sound-field imaging mainly due to its low imaging quality, it has several desired properties, including thinness, lightweight, low cost, and ease of making a large aperture. We constructed an optical holographic imaging system composed of two Fresnel lenses used for magnification and demagnification of the illuminating beam. A proof-of-concept experiment verified that the sound-field imaging with Fresnel lenses is possible by using the spatiotemporally harmonic nature of sound.

Three-dimensional localization of gas leakage using acoustic holography

Gas leakage localization is essential to prevent accidents from gas transportation or storage failures. There have been extensive studies on one-dimensional (1D) and two-dimensional (2D) gas leakage localization problem. This paper is the first to report the demonstration of a three-dimensional (3D) localization of gas leaks using far-field acoustic holography. This approach simultaneously provides 2D sound field imaging and depth position information regarding the leakage source. A virtual phased array composed of only two sensors collects the needed data, resulting in improved accuracy, enhanced feasibility and reduced cost. Various parameters, including the number of sensors, the spacing of array elements and the distance to the leakage source, are analyzed by a simulation of leakage sound field reconstruction. A series of experiments validated the effectiveness and accuracy of the proposed approach. Our results demonstrate that the proposed method achieves 3D localization and high-resolution imaging recognition of gas leaks.

Multimodal sound field imaging using digital holography [Invited

Sound is an important invisible physical phenomenon that needs to be explained in several physical and biological processes, along with visual phenomena. For this purpose, multiparameter digital holography (DH) has been proposed to visualize both features simultaneously due to the phase and amplitude reconstruction properties of DH. In this paper, we present a brief review on sound field imaging techniques with special focus on the multiparameter imaging capability of DH for visualizing sound and visual features. The basic theory and several experimental results with very high-speed recordings are also presented to demonstrate sound field imaging for the audible range as well as in the ultrasound range.

A Coupling Graphic Pipeline with Normal Mode Model for Rapid Calculation of Underwater Acoustic Field

Rapid execution is required in operation-oriented applications in underwater acoustic modelling. In this paper, the GPU graphic pipeline is used to accelerate the calculation of high-resolution sound field image in the normal mode model of underwater acoustic propagation. The computer times of the proposed graphic pipeline method, the MATLAB code, and the C# code are compared for a stratified shallow water waveguide using the KRAKEN model at different frequencies. The research validates that the graphic pipeline method outperforms the classic CPU-based methods in terms of execution speed at the frequencies where the eigenvalue equation in normal mode models can be solved.

High-speed imaging of the sound field by parallel phase-shifting digital holography.

Sound field imaging techniques have been found very useful for acoustic designs. Building on this idea, innovative techniques are needed and presented in this paper, where we report on developed imaging of the sound field radiated from speakers by parallel phase-shifting digital holography. We adopted an ultrasonic wave radiated from a speaker for an object. The phase distribution of the light wave was modulated by the sound field radiated from the speaker. The modulated phase distribution was recorded in the form of multiplexed phase-shifted holograms at the frame rate of 100,000 fps. A 40,000 Hz sound field radiated from a speaker is used as an observation target. Our proposed method can implement the imaging of the sound field successfully. Also, in order to demonstrate the digital refocusing capability of digital holography, we set two speakers, whose difference in depth positions was 6.6 cm, as a long-depth object. We demonstrated the digital refocusing on the two speakers along with the capability of measuring the positions of the objects. Furthermore, we succeeded in imaging of 40,000 Hz and 41,000 Hz sound fields radiated from the two speakers. The presented experimental results showed that parallel phase-shifting digital holography is very useful and suitable for sound field imaging.

Single-shot common-path off-axis digital holography: applications in bioimaging and optical metrology [Invited

The demand for single-shot and common-path holographic systems has become increasingly important in recent years, as such systems offer various advantages compared to their counterparts. Single-shot holographic systems, for example, reduce computational complexity as only a single hologram with the object information required to process, making them more suitable for the investigation of dynamic events; and common-path holographic systems are less vibration-sensitive, compact, inexpensive, and high in temporal phase stability. We have developed a single-shot common-path off-axis digital holographic setup based on a beam splitter and pinhole. In this paper, we present a concise review of the proposed digital holographic system for several applications, including the quantitative phase imaging to investigate the morphological and quantitative parameters, as a metrological tool for testing of micro-optics, industrial inspection and measurement, and sound field imaging and visualization.

A Microscale Linear Phased-Array Ultrasonic Transducer Based on PZT Ceramics.

In this paper, a microscale high-frequency ultrasonic transducer was prepared by combining traditional planar ultrasonic phased-array technology and micro processing technology. The piezoelectric ceramic material PZT was used as the functional material of the transducer. The number of the arrays was 72, the width of each array was 50 μm, the pitch of each array was 70 μm, and the length of each array was 3 mm. The PZT chip was finely ground to a thickness of 130 μm and could reach a frequency of 10 MHz. The experimental platform of micron-scale precision was set up for a beam-forming lateral sound field test and imaging experiment to validate the theoretical analysis. The echo imaging test showed that a mold with a feature size of about 400 μm could be imaged well.

Characteristics of vibration frequency measurement based on sound field imaging by digital holography

We present the characteristics of indirect frequency measurement system based on off-axis digital holography (DH) for vibrating objects, which works on phase change characteristics of a medium where sound wave propagates. The sound field measurement method using off-axis DH already proposed by the author’s group is applied to the measurement of vibration frequency of arbitrary sound sources. In DH based sound imaging for frequency measurement, object wave passes near to vibrating object and the interference patterns are recorded in digital holograms as a function of time. After using inverse Fresnel calculation, acousto-optic data processing, and Fourier analysis, vibration frequency of an object of interest can be measured. In this paper, the measurement capability of vibration frequency for different objects and quantitative characteristics of the sound power are evaluated experimentally. The frequency range of the experimental results are from hundreds Hz to tens of kHz that covers audible range. The comparison with microphone recording and the analysis have also been carried out to check the strength and stability of the proposed scheme.

Full-spectrum near-field acoustical holography for fighter jet noise imaging

The development of acoustic imaging technologies over the previous decade has proven useful for increasing our understanding of the noise generation mechanisms inside the turbulent flows of full-scale tactical aircraft engines. In particular, advancements in near-field acoustical holography have allowed for jet noise source imaging from measurements made on tied-down aircraft over hard reflecting ground surfaces. These images have been limited in bandwidth due to the spatial resolution and extent of the holography arrays. However, improved aperture extension methods have allowed for representation of the lowest frequencies, and a new tool has been developed to produce accurate sound field images at above-Nyquist frequencies for broadband sources. These two technologies are implemented together to extend the imaging of fighter jet noise near-field toward the full spectrum required for an aircraft noise model.The development of acoustic imaging technologies over the previous decade has proven useful for increasing our understanding of the noise generation mechanisms inside the turbulent flows of full-scale tactical aircraft engines. In particular, advancements in near-field acoustical holography have allowed for jet noise source imaging from measurements made on tied-down aircraft over hard reflecting ground surfaces. These images have been limited in bandwidth due to the spatial resolution and extent of the holography arrays. However, improved aperture extension methods have allowed for representation of the lowest frequencies, and a new tool has been developed to produce accurate sound field images at above-Nyquist frequencies for broadband sources. These two technologies are implemented together to extend the imaging of fighter jet noise near-field toward the full spectrum required for an aircraft noise model.

Sound field reconstruction within an entire cavity by plane wave expansions using a spherical microphone array.

A spherical microphone array has proved effective in reconstructing an enclosed sound field by a superposition of spherical wave functions in Fourier domain. It allows successful reconstructions surrounding the array, but the accuracy will be degraded at a distance. In order to extend the effective reconstruction to the entire cavity, a plane-wave basis in space domain is used owing to its non-decaying propagating characteristic and compared with the conventional spherical wave function method in a low frequency sound field within a cylindrical cavity. The sensitivity to measurement noise, the effects of the numbers of plane waves, and measurement positions are discussed. Simulations show that under the same measurement conditions, the plane wave function method is superior in terms of reconstruction accuracy and data processing efficiency, that is, the entire sound field imaging can be achieved by only one time calculation instead of translations of local sets of coefficients with respect to every measurement position into a global one. An experiment was conducted inside an aircraft cabin mock-up for validation. Additionally, this method provides an alternative possibility to recover the coefficients of high order spherical wave functions in a global coordinate system without coordinate translations with respect to local origins.

The Ray Space Transform: A New Framework for Wave Field Processing

Soundfield imaging is a special analysis methodology aimed at capturing the directional components of the acoustic field and mapping them onto a domain called “ray space”, where relevant acoustic objects become linear patterns, i.e., sets of collinear points. This allows us to overcome resolution issues while easing far-field assumptions. In this paper, we generalize this concept by introducing the ray space transform for acoustic field representation. The transform is based on a short space-time Fourier transform of the signals captured by a microphone array, using discrete Gabor frames. The resulting transform coefficients are parameterized in the same ray space used for soundfield imaging. The resulting transform enables the definition of analysis and synthesis operators, which exhibit perfect reconstruction capabilities. We show examples of applications of the ray space transform to source localization and spot spatial filtering.

Optical sensing of sound fields: Non-contact, quantitative, and single-shot imaging of sound using high-speed polarization camera

Imaging of a sound field aids understanding of the actual behavior of the field. That is useful for obtaining acoustical spatial characteristics of transducers, materials and noise sources. For high spatial resolution imaging, optical measurement methods have been used thanks to its contactless nature. This paper presents sound field imaging method based on parallel phase-shifting interferometry, which enables to acquire an instantaneous two-dimensional phase distribution of light. Information of sound field is calculated from the phase of light based on the acousto-optic theory. The system consists of a polarization interferometer and high-speed polarization camera. The number of the measurement points in a single image are 512 × 512 and the interval between adjacent pixels is 0.22 mm. Therefore, the system can image a sound field with much higher spatial resolution compared with conventional imaging methods such as microphone arrays. The maximum frame rate, which is corresponding to the sampling frequen...

High-speed imaging of sound using parallel phase-shifting interferometry.

Sound-field imaging, the visualization of spatial and temporal distribution of acoustical properties such as sound pressure, is useful for understanding acoustical phenomena. This study investigated the use of parallel phase-shifting interferometry (PPSI) with a high-speed polarization camera for imaging a sound field, particularly high-speed imaging of propagating sound waves. The experimental results showed that the instantaneous sound field, which was generated by ultrasonic transducers driven by a pure tone of 40 kHz, was quantitatively imaged. Hence, PPSI can be used in acoustical applications requiring spatial information of sound pressure.

Sound field imaging by using optical system

Sound field imaging by using optical system

Analytical modeling, finite-difference simulation and experimental validation of air-coupled ultrasound beam refraction and damping through timber laminates, with application to non-destructive testing

Reliable non-destructive testing (NDT) ultrasound systems for timber composite structures require quantitative understanding of the propagation of ultrasound beams in wood. A finite-difference time-domain (FDTD) model is described, which incorporates local anisotropy variations of stiffness, damping and density in timber elements. The propagation of pulsed air-coupled ultrasound (ACU) beams in normal and slanted incidence configurations is reproduced by direct definition of material properties (gas, solid) at each model pixel. First, the model was quantitatively validated against analytical derivations. Time-varying wavefronts in unbounded timber with curved growth rings were accurately reproduced, as well as the acoustic properties (velocity, attenuation, beam skewing) of ACU beams transmitted through timber lamellas. An experimental sound field imaging (SFI) setup was implemented at NDT frequencies (120kHz), which for specific beam incidence positions allows spatially resolved ACU field characterization at the receiver side. The good agreement of experimental and modeled beam shifts across timber laminates allowed extrapolation of the inner propagation paths. The modeling base is an orthotropic stiffness dataset for the desired wood species. In cross-grain planes, beam skewing leads to position-dependent wave paths. They are well-described in terms of the growth ring curvature, which is obtained by visual observation of the laminate. Extraordinary refraction phenomena were observed, which lead to well-collimated quasi-shear wave coupling at grazing beam incidence angles. The anisotropic damping in cross-grain planes is satisfactorily explained in terms of the known anisotropic stiffness dataset and a constant loss tangent. The incorporation of high-resolution density maps (X-ray computed tomography) provided insight into ultrasound scattering effects in the layered growth ring structure. Finally, the combined potential of the FDTD model and the SFI setup for material property and defect inversion in anisotropic materials was demonstrated. A portable SFI demonstrator was implemented with a multi-sensor MEMs receiver array that captures and compensates for variable wave propagation paths in glued laminated timber, and improves the imaging of lamination defects.