Acoustic Modulation Research Articles

Acoustic‐Modulated, Selective Particle Deposition for Muti‐Material Additive Manufacturing

AbstractPowder‐based additive manufacturing (AM) is an important technology in fabricating complex 3D products. In powder‐based AM, a powder deposition system plays a key role in determining the resolution, density, and properties of printed parts. An acoustic‐actuated particle deposition approach, which utilizes acoustic waves to actuate a glass nozzle, enables the deposition of particles in a cost‐effective way. However, the capability to programmably deposit different particles using acoustic waves has yet to be fully demonstrated. Herein, a selective particle deposition approach via acoustic modulation for muti‐material AM is demonstrated. Sequential and parallel depositions of two types of particles by modulating the signal inputs and resonant frequencies of piezo transducers are demonstrated. An AM process is demonstrated by integrating this acoustic‐actuated particle deposition approach with a heat‐curing mechanism. Several products from this system are produced as well. It is expected that this particle deposition approach can be used in a wide spectrum of applications, such as direct manufacturing of multi‐functional materials/devices.

Implications of liquid impurities filled in breaking cracks on nonlinear acoustic modulation response: Mechanisms, phenomena and potential applications

Supervised strategies for ultrasonic-based cracks detection in existing structures has been one of particular concerns in the engineering community. However, current researches mostly focus on the clean microcracks, while ignoring the fact that such cracks will be contaminated with liquid impurities (lubricants, silicone oil, etc.) due to its exposure to the operational environment. Actually, the presence of liquid may lead to a non-negligible change in the acoustic performance and interfere with damage diagnosis. The central contribution of this work is to reveal the nonlinear acoustic mechanisms and phenomena induced by the gas–liquid–solid coupling interfaces in such liquid-filled cracks and investigate their potential applications for such crack detection. Firstly, the state equation for a liquid-filled cavity in beams is established to determine the nonlinear dependences of stress–strain relationship at crack wall on the viscous and capillary pressure in liquid. Secondly, a modified acoustic modulation method, in which swept signal is used as the pumping wave to sufficiently trigger and enhance the nonlinear behaviours at the gas–liquid–solid interfaces without requiring exact reference information, is utilized for detecting sub-millimeter cracks filled with different liquid. The results suggest that the liquid fillers may cause considerable increase of the damage-related acoustic nonlinearities involving hysteresis nonlinearity, nonlinear elastic behavior and dissipative nonlinearity. Additional analysis provides compelling evidence for the following valuable conclusions: 1) the capillary pressure is a key factor that promotes conducive to the nonlinear elastic behavior that is the primary source of the first-order sum-difference frequency; 2) the viscous pressure contributes to hysteresis as well as the nonlinear dissipation, and the latter promotes the second-order sum frequency. Further, such nonlinear performance especially dissipation offer promising prospects for nonlinear acoustic diagnostic of such cracks. All results obtained in this study will aid in understanding the nonlinear wave processes and further improving the reliability of crack detection in engineering.

Compensating three-dimensional field inhomogeneity in cold atom Efimov-state search by a time-averaged optical potential.

The Efimov effect and its universal property are of paramount importance in quantum few-body physics. Despite this, the predicted ground state Efimov resonance has not yet been observed in 39,40,41K-87Rb mixtures within the currently available observation window. Cooling atoms in the microgravity environment of outer space might overcome this limitation, whereas the residual curvature of the strong magnetic fields may result in significant atom leakage. In this work, we propose an optical method based on far-detuned time-averaged dipole potential to counteract the three-dimensional inhomogeneous field. The target intensity distribution can be conveniently obtained by modulating the central position of the quasi-1D print beam using acoustic optical modulators. Within a volume of 300 × 300 × 400µm3, the residual potential fluctuations can be reduced by two orders of magnitude to less than 100 pK. The proposed approach offers a realistic prospect of investigating the Efimov-type resonance in the 40K-87Rb Bose-Fermi mixture.

Neural speech tracking shifts from the syllabic to the modulation rate of speech as intelligibility decreases.

The most prominent acoustic features in speech are intensity modulations, represented by the amplitude envelope of speech. Synchronization of neural activity with these modulations supports speech comprehension. As the acoustic modulation of speech is related to the production of syllables, investigations of neural speech tracking commonly do not distinguish between lower-level acoustic (envelope modulation) and higher-level linguistic (syllable rate) information. Here we manipulated speech intelligibility using noise-vocoded speech and investigated the spectral dynamics of neural speech processing, across two studies at cortical and subcortical levels of the auditory hierarchy, using magnetoencephalography. Overall, cortical regions mostly track the syllable rate, whereas subcortical regions track the acoustic envelope. Furthermore, with less intelligible speech, tracking of the modulation rate becomes more dominant. Our study highlights the importance of distinguishing between envelope modulation and syllable rate and provides novel possibilities to better understand differences between auditory processing and speech/language processing disorders.

Viability of COMSOL within the silencer selection process

Silencer selection has long been a burdensome, and occasionally iterative process. It is typically done based on tested sound attenuation values obtained using large facilities and costly equipment - making the process time-consuming and unsustainable. Fortunately, Finite Element Analysis (FEA) continues to become a more viable intermediary step between design and construction. COMSOL Multiphysics(r) is an FEA solver and simulation software. COMSOL's acoustics module can determine full octave decibel values of Transmission Loss.This paper goes through parameters and model setup in the COMSOL environment as well as the practicality and convenience of using such a software. It also investigates the reliability of such methods of acoustic analysis compared to empirical data, where it may fall short, and identifies areas in need of more analysis.

Acoustic modelling of 3D-printed hybrid materials: a preliminary study

Analytical and finite element (FE) models are developed to predict the sound absorption coefficient of hybrid materials obtained through assembly of folded quarter-length resonators and periodic porous material. The analytical model uses the sum of the acoustic admittances. The acoustic admittance of resonators is simulated with Stinson's model. Johnson-Champoux-Allard-Lafarge (JCAL) model and transfer matrix method (TMM) are used to calculate the acoustic admittance of 1, 2 and 4-layers of porous materials with different geometric parameters. The FE model is implemented using the COMSOL Multiphysics. The helical tubes are simulated using the visco-thermal acoustic module while the porous layers are simulated with JCAL poro-acoustic module. 30-mm thick samples of hybrid materials are produced via additive manufacturing (AM). Normal incident sound absorption coefficient of the hybrid materials is measured using an impedance tube. The experimental and simulated sound absorption coefficients are compared. The impact of the structure parameters (resonator diameter and length as well as number of porous layers) on the sound absorption is assessed. The hybrid materials present low frequency and broadband sound absorption. Higher broadband sound absorption is obtained with 4-layers of porous material. Low frequency absorption ( 1000 Hz) is achieved with long folded resonators (L 100 mm).

Electro-Acoustic Phase Modulator Based on AlScN Thin Film

Acoustic waveguides and ring resonators based phononic integrated circuits (PnIC) have attracted more and more attention due to potential applications in the quantum system and signal processing. However, there are very few studies on active modulation utilizing electro-acoustic (EA) effect. PnIC requires efficient modulation components as well as a high electromechanical coupling platform. Here we demonstrate an acoustic wave phase modulator based on AlScN thin film. The acoustic wave phase of proposed AlScN thin film devices can be controlled through the driving voltage, modulation length as well as the acoustic wavelength. A π phase shift is obtained at an amplitude of 62.5 V DC bias on an acoustic waveguide of 100 μm long at the acoustic wave of approximately 1.975 GHz, i.e., Vπ∙L = 6.25*10-3 V∙m. Moreover, acoustic frequency combs and serrodyne frequency translators have been demonstrated. Such high performance AlScN thin film EA phase modulator proves a new PnIC platform for future hybrid chip-scale phonon transduction and signal processing.

Adaptive Underwater Acoustic OFDM Modulation Method Based on Improved Deep Reinforcement Learning

High environmental noise, narrow bandwidth, low carrier frequency, large transmission delay and other factors restrict the data transmission rate in underwater acoustic communication. To this end, improving communication quality and efficiency through adaptive adjustment is necessary for underwater acoustic communication system because of the restrict factor. The proposed method uses Deep Reinforcement Learning (DRL) to select the optimal transportation parameters and maximize the transmission efficiency with. The adaptive communication parameter setting is mapped into a Markov decision process with an unknown state transition probability. The system returns channel information including Channel State Information (CSI) and Signal Noise Ratio (SNR). We validate our estimation and adaptation techniques using the well-known simulator SWellEx_96 in varying underwater environments. Our results show that, for many practical cases, a dynamic adjustment of the prefix length, number of sub-carriers, filter length, and over-sampling factor may enable the utilization of OFDM modulations in underwater communications.

An Approach for Automated Kannada Subtitle Generation from Kannada Video

This paper presents an automated Kannada subtitle generator from Kannada video which is implemented to assist people with auditory problems for watching videos. Henceforth the subtitle generation has become an important task for supporting such special people and it integrates an audio extraction and a speech recognition module. Three phases of the proposed technique were implemented, such as extracting audio from video, Recognition of Speech and Generation of Subtitle. An adaptive speech recognition module is implemented AMFCC for feature extraction which was an alternative to the most commonly used FFT. Hankel transform which was similar to FFT, but includes no elementary particles such as FFT. In addition to it, in the decoder acoustic module, such as Adaptive Hidden Markov Model using the Baum-Welch algorithm is utilized instead of a Viterbi algorithm to reduce the computational time and memory usage. The text file from the speech recognition module is rendered to synchronize the missing offset with the video using parallel processing by defining the start time, the end time, the delay time. Best outcomes are demonstrated by the experimental results of the proposed technique with 98.4% of accuracy compare with existing techniques. The proposed technique which gives 3.8% better accuracy performance compare with existing technique i.e. MFCC, DNN and CNN.

How to hide your voice: noise-cancelling bird photography blind

Getting close to birds is a great challenge in wildlife photography. Bird photography blinds may be the most effective and least intrusive way if properly designed. However, the acoustic design of the blinds has been overlooked so far. Herein, we present noise-cancelling blinds which allow photographing birds at close range. First, we conducted a questionnaire in the eco-tourism centre located in Yunnan, China. Thus, the birders' expectations of the indoor sound environment are determined. We then identify diverse variables to examine the impact of architectural and acoustic decisions on noise propagation. Finally, the acoustic performances of the blinds by considering the birds' hearing threshold are examined. The numerical simulations are performed in the acoustics module of Comsol MultiPhysics. Our study demonstrated that photography blinds require a strong and thorough acoustic design for both human and bird well-being.

Acoustic communication and imaging sonar guided AUV docking: system infrastructure, docking methodology and lake trials

Autonomous underwater vehicle (AUV) docking technique attracts attention which leverages the long-term, on-station vehicle launch and recovery for the underwater missions. In this paper, an acoustic communication and imaging sonar guided docking method is proposed to improve the docking accuracy for AUV. In docking system, multibeam forward looking sonar (MFLS) is deployed on the submerged docking station to reduce the noise in acoustic images rather than being fixed on AUV, and the ultra short base line (USBL) transceiver with acoustic communication modules is used to achieve positioning while AUV is out of the view of MFLS. For the docking methodology, a dedicated three-stage docking strategy is presented to guide AUV to the docking station. In the homing stage, AUV navigates to a preset homing place not very far from the docking station via the way-point guidance and self-positioning of the on-board inertial navigation system (INS). In the next stage, USBL provides the relative position for AUV controller via acoustic channel. Moreover, an exponential decay model based filtering algorithm is proposed to eliminate the positioning outliers of USBL. It is expected that AUV will be guided into the perceptual field of MFLS in this stage. In the final stage, the docking accuracy in short range should be improved while USBL may generate outliers due to the louder noise. In this case, the relative positioning is implemented by using kernelized correlation filter (KCF), which is a fast objective tracking algorithm to keep track of the AUV feature in acoustic image until AUV navigates into the docking station or out of the view of sensor. To validate feasibility and performance of the proposed system infrastructure and docking methodology, the docking results are analyzed by contrast with the experiments only use USBL during lake trials.

The extreme bulk-modulus contrast of bubbly soft matter for underwater acoustic modulation

Bubbles in liquid and soft matter are excellent acoustic resonators with extremely low resonant frequencies. We find that bubbly soft matter (BSM) can enable full-phase (2π) modulation of incident acoustic waves just through changing the bubble size. Compared with the conventional solid–solid binary locally resonant metamaterial (SSM), due to the extreme bulk-modulus ratio of the bubbles and the soft matrix, the BSM has two distinguished merits. First, the size of the bubbly inclusions for the full-phase modulation is only about a third of the solid inclusions in the SSM; second, the range of variation of the bubbly inclusions to cover the full-phase modulation is two orders of magnitude wider than that of the solid inclusions. These features, combined with the salient advantage of wave-impedance match between soft matter and water, can realize compact and light-weight reflective and transmissive underwater bubble metasurfaces. At the lower limit 3 kHz of the active sonar operating frequency, an ultrathin reflective metasurface with a thickness of 1/50 the wavelength can redirect the incident waves at a given angle. Bubble resonance in soft matter opens a new avenue for underwater acoustic modulation at the deepest subwavelength.

Quartz‐Enhanced Photoacoustic Sensors for Detection of Eight Air Pollutants

A quartz‐enhanced photoacoustic spectroscopy sensor architecture capable of detecting eight different air pollutants (CH4, NO2, CO2, N2O, CO, NO, SO2, and NH3) is reported. Each analyte is targeted using the same sensor components (acoustic detection module, quartz‐tuning fork, etc.) and a dedicated laser source. Both interband cascade lasers and quantum cascade lasers are employed to target a well‐resolved and isolated absorption feature from each investigated gas, in a wavelength ranging from 3.35 to 9.06 μm. The sensor is calibrated with certified concentrations of each gas species, in a wet nitrogen matrix. For each analyte, the optimal pressure is determined. Minimum detection limits of 40, 13, 800, 230, 450, 78, 18, and 5.8 ppb are obtained for CH4, NO2, CO2, N2O, CO, NO, SO2, and NH3, respectively, at 100 ms of integration time.

Focus on software, data acquisition, and instrumentation

Focus on software, data acquisition, and instrumentation

Noninvasive Skin Respiration (CO2) Measurement Based on Quartz-Enhanced Photoacoustic Spectroscopy.

A noninvasive method for disease diagnosis that does not require complex specialized laboratory facilities and chemical reagents is particularly attractive in the current medical environment. Here, we develop a noninvasive skin respiration sensor based on quartz-enhanced photoacoustic spectroscopy (QEPAS) that can monitor the skin elimination rate of carbon dioxide (CO2). A 3.8 mW distributed feedback laser emitting at 2.0 μm is used as an excitation source, and a three-dimensional (3D)-printed acoustic detection module is designed to apply to the skin as a sensor head. The performance of the noninvasive skin respiration sensor is assessed in terms of detection sensitivity, linearity, long-term stability, and water effect. A minimum detection limit of 35 ppb is achieved at the optimal integration time of 670 s. The skin respiration measurements from eight healthy volunteers are recorded, and the real-time results are analyzed.

Simplified calculation method for hydrodynamic noise of multi-tube heat exchanger based on acoustic cavity model

Because of the complex structure of the heat exchanger, its hydrodynamic noise simulation is difficult and the problem of low computational efficiency can not be solved well. An acoustically simplified calculation method for a large shell and tube heat exchanger with 2000 heat transfer tubes is proposed for a multi-tube number heat exchanger. The heat exchanger tubes are equated to different numbers of heat exchanger tubes according to their through-flow areas of 2000 heat exchanger tubes. Based on the LMS Virtual.Lab acoustic finite element module, acoustic cavity model calculations and analysis are performed for heat exchangers with different numbers of heat transfer tubes. From the acoustic cavity model laws of heat exchangers with 20, 100, 500 and 1000 tubes, it can be found that the distribution of vibration patterns and the intrinsic frequencies of heat exchangers with different tube numbers are similar. Therefore, the calculation model of 20 heat exchanger tubes is selected for noise calculation based on the fluid calculation software ANSYS-CFX and the acoustic calculation software ACTRAN. Based on the results of the noise calculation and the comparison verification of the experimental data, it is concluded that the heat exchanger models with similar acoustic cavity model have similar sound pressure levels. In addition, the sound transmission loss law and the contribution of the acoustic cavity model of the shell and tube heat exchanger are analyzed. Therefore, the effectiveness of the simplified calculation method of multi-tube number heat exchanger proposed is verified. The proposed simplified calculation method can be used to reduce the calculation difficulty and improve the calculation efficiency of complex heat exchangers.

A Comparison of the Performance of Four Acoustic Modulation Techniques for Robot Communication in Pipes

Autonomous robotics is an emerging technology for the inspection of a vast network of underground pipes. Communication between autonomous robots is essential to optimise their efficiency and network coverage. However, sending a message acoustically is not a well-researched topic because most of the existing literature is devoted to the study of the acoustic properties of the pipe for the purpose of sensing rather than communication. In particular, the influence of multi-modal propagation and background noise on the quality of acoustic communication in pipes has not been well understood. This paper studies the performance of four standard acoustic communication techniques in a dry drainage pipe to fill this knowledge gap. The noise resistance, communication range and data rate of these techniques are estimated through numerical simulations and laboratory experiments. It has been found that the techniques based on shift keying requires at least 5--10 dB signal to noise ratio (SNR) to function properly while the chirp linear frequency modulation technique can operate reliably with SNR = 0 dB or event lower SNR. The results also suggest that the multi-modal propagation in the pipe has significant effects on the package error rate. The frequency dependent sound attenuation in the pipe also affects the communication range and data rate. In particular, for a 150 mm diameter dry pipe the maximum robot operation distance is likely to be limited to 50--100 m with the highest carrier frequency of around 10 kHz and data rates below 6300 bps. The results of this work pave the way to the development of acoustic communication modules to be deployed on tetheless robots designed to inspect a buried pipe network autonomously and collaboratively.

Modulation Signal Recognition of Underwater Acoustic Communication Based on Archimedes Optimization Algorithm and Random Forest

This paper researches the recognition of modulation signals in underwater acoustic communication, which is the fundamental prerequisite for achieving noncooperative underwater communication. In order to improve the accuracy of signal modulation mode recognition and the recognition effects of traditional signal classifiers, the article proposes a classifier based on the Archimedes Optimization Algorithm (AOA) and Random Forest (RF). Seven different types of signals are selected as recognition targets, and 11 feature parameters are extracted from them. The decision tree and depth obtained by the AOA algorithm are calculated, and the optimized random forest after the AOA algorithm is used as the classifier to achieve the recognition of underwater acoustic communication signal modulation mode. Simulation experiments show that when the signal-to-noise ratio (SNR) is higher than -5dB, the recognition accuracy of the algorithm can reach 95%. The proposed method is compared with other classification and recognition methods, and the results show that the proposed method can ensure high recognition accuracy and stability.

Automatic detection of nasalization in speech via cue-based analysis

Modern speech recognition systems are powerful, but it is not simple to understand the mechanisms by which they model speech, or precisely how they make use of acoustic cues. Moreover, a system for the explicit detection of individual acoustic cues may be useful not only for speech recognition but for understanding the principles that govern sub-phonemic patterns of surface-phonetic variation, and how specific cue patterns may reflect speech disorders. This report describes a transparent, acoustic cue-based nasalization detection module, that can be used to find not only nasal consonants but also nasalization wherever it appears, e.g., within a vocalic region. We lay out a framework for extracting measurements that are key to detecting nasalization, in particular, the nasality-related spectral peaks P0 and P1, and confirm the utility of these measurements for nasality detection in spoken words. In particular, we present a pre-processing and cue-value extraction framework, and propose a Gaussian Mixture Model-based approach to detect the regions of nasalization in a speech signal. This work on a detection module for nasalization is part of a larger effort to develop a speech recognition system that is based on landmarks and other acoustic cues.

Research on Acoustic Reflection Characteristics of Typical Concave Body based on COMSOL

In the design of an underwater acoustic imaging system, to improve the signal-to-noise ratio (Snr) of the signal receiver and achieve good acoustic imaging results, it is necessary to discuss the acoustic focusing problem of the concave body. Based on COMSOL finite element analysis, this paper makes a comparative analysis of concave structures in several typical acoustic reflection modules, takes plane waves as the background sound field, analyses the acoustic reflection performance of typical concave structures at different wavelengths and angles of incidence, and studies the acoustic convergence effect under different concave structures, providing reference and help for further optimizing the design of acoustic imaging systems.