Acoustic Microphone Research Articles

Recent investigation on VHF sound exposure sources around us

We have reported recent investigation of sound exposure sources in very-high frequency (VHF) region as the activities for research project of VHF sounds in Japan. Recently, the devices which utilize or generate VHF sounds as like rodent repelling devices, ultrasonic cleaning machines, IH cookers and corner sensors of automobile continue to increase in public space or our living environment. The VHF sounds in high level have physical or/and psychological effects for young people who can hear such sounds. So, in environment around us, we identified VHF sound sources using acoustic camera and measured the sound pressure level for such sources. In this paper, we introduce newly-discovered several VHF sounds: for example, ultrasounds from corner sensors of automobile car, VHF sounds from photovoltaic installation and VHF sounds of interior train, and so on. From both the results measured by acoustic camera and microphones show source positions and frequency characteristics of VHF sounds. However these play important role in our life environment, we need to note that these contain potential hazard for young people who can hear such VHF sounds.

Accurate Modeling of Ejection Fraction and Stroke Volume With Mobile Phone Auscultation: Prospective Case-Control Study.

Heart failure (HF) contributes greatly to morbidity, mortality, and health care costs worldwide. Hospital readmission rates are tracked closely and determine federal reimbursement dollars. No current modality or technology allows for accurate measurement of relevant HF parameters in ambulatory, rural, or underserved settings. This limits the use of telehealth to diagnose or monitor HF in ambulatory patients. This study describes a novel HF diagnostic technology using audio recordings from a standard mobile phone. This prospective study of acoustic microphone recordings enrolled convenience samples of patients from 2 different clinical sites in 2 separate areas of the United States. Recordings were obtained at the aortic (second intercostal) site with the patient sitting upright. The team used recordings to create predictive algorithms using physics-based (not neural networks) models. The analysis matched mobile phone acoustic data to ejection fraction (EF) and stroke volume (SV) as evaluated by echocardiograms. Using the physics-based approach to determine features eliminates the need for neural networks and overfitting strategies entirely, potentially offering advantages in data efficiency, model stability, regulatory visibility, and physical insightfulness. Recordings were obtained from 113 participants. No recordings were excluded due to background noise or for any other reason. Participants had diverse racial backgrounds and body surface areas. Reliable echocardiogram data were available for EF from 113 patients and for SV from 65 patients. The mean age of the EF cohort was 66.3 (SD 13.3) years, with female patients comprising 38.3% (43/113) of the group. Using an EF cutoff of ≤40% versus >40%, the model (using 4 features) had an area under the receiver operating curve (AUROC) of 0.955, sensitivity of 0.952, specificity of 0.958, and accuracy of 0.956. The mean age of the SV cohort was 65.5 (SD 12.7) years, with female patients comprising 34% (38/65) of the group. Using a clinically relevant SV cutoff of <50 mL versus >50 mL, the model (using 3 features) had an AUROC of 0.922, sensitivity of 1.000, specificity of 0.844, and accuracy of 0.923. Acoustics frequencies associated with SV were observed to be higher than those associated with EF and, therefore, were less likely to pass through the tissue without distortion. This work describes the use of mobile phone auscultation recordings obtained with unaltered cellular microphones. The analysis reproduced the estimates of EF and SV with impressive accuracy. This technology will be further developed into a mobile app that could bring screening and monitoring of HF to several clinical settings, such as home or telehealth, rural, remote, and underserved areas across the globe. This would bring high-quality diagnostic methods to patients with HF using equipment they already own and in situations where no other diagnostic and monitoring options exist.

A new approach to monitoring solvent extraction processes for the nuclear industry

As part of an initiative to steward research, development, and innovation into the nuclear fuel cycle, Idaho National Laboratory is building the Beartooth test bed. Beartooth will include a cascade of centrifugal contactors, glove box lines, and solidification and dissolution equipment to aid in the progression of novel separation techniques and to provide hands-on opportunities to early-career separation engineers. Beartooth will incorporate novel monitoring techniques using sensors and machine learning algorithms to inform process operators of separation conditions. This research is examining unconventional monitoring technologies such as incorporating acoustic microphones, vibration sensors, infrared cameras, red-green-blue color sensors, among others into nuclear separation processes. Research is ongoing in the use of machine learning methods to detect faults and alert operators of typical and anomalous events. Results from this research have the potential to impact safeguards-by-design efforts and real-time decision making. This overview will detail preliminary measurement results from acoustic, vibration, and color sensors.

Optical fiber-based acoustic intensity microphone for high-intensity airborne ultrasound measurement

The increasing use of airborne ultrasonic waves in daily life, driven by advances in parametric and phased arrays, has led to innovative applications like highly directional speakers, non-contact tactile feedback, 3D acoustic levitation, and medical therapies. These advancements necessitate accurate measurement of high-intensity ultrasonic waves, exceeding the capability of traditional microphones limited to around 160 dB, and highlight the growing importance of measuring the sound field not merely as scalar (sound pressure) but as vector (acoustic intensity) to accommodate future technological developments. This paper introduces an acoustic intensity microphone using optical fibers as probes to overcome these limitations. The proposed method replaces the two ordinary microphones used in the traditional acoustic intensity measurement method with thin optical fibers, minimizing sound field disturbance. Experimental validation and the structure of a practical acoustic intensity microphone are discussed, building upon foundational work presented at USE2023 with added verification and insights.

Strengths and weaknesses of acoustic pipe microphone systems in ephemeral, sandy, gravel‐bed rivers

AbstractWe calibrated an acoustic pipe microphone system to monitor bedload flux in a sandy, gravel‐bed ephemeral channel. Ours is a first attempt to test the limit of an acoustic surrogate bedload system in a channel with a high content of sand. Calibrations varied in quality; significant data subsetting was required to achieve R2 values &gt;0.75. Several data quality issues had to be addressed: (1) apparent pulses, which occur when a sensor records an impulse from sediment impacting the surrounding substrate rather than directly impacting the sensor, were frequent, especially at higher signal amplifications. (2) The impact sensors were frequently covered by gravel sheets. This prompted the development of a cover detection protocol that rejected part of the impact sensor record when at least one sensor was partially or fully covered. (3) Because of the lack of sensor sensitivity to impacts of sand‐sized particles, which was anticipated, and the considerable sand component of bedload in this channel, a grain size‐limited bedload flux was estimated. This was accomplished by sampling the bedload captured by slot samplers and evaluating the variation of grain size with increasing flow strength. This considerably improved the results when compared to attempts at estimating the flux of the entire distribution of grain sizes. This calibration is a successful first attempt, though the impact sensors required several site‐specific calibration steps. A universal set of equations using impact sensors to estimate bedload transport of fine‐gravel with a large content of sand remains elusive. Notwithstanding, our study demonstrates the utility of impact sensor data, producing relatively low root mean square errors that are independent of measurements of flow strength (i.e. discharge). These tools will be particularly useful in settings that would benefit from new methodologies for estimating bedload transport in sand‐rich gravel‐bed rivers, such as the American desert Southwest.

Coherence between error and acoustic reference microphones with two closely located noise sources

It is well known that locating acoustic reference microphones near the error microphone can improve the coherence between reference and error signals in feedforward active noise control systems. In this paper, the effects of the number of reference microphones and the distance between noise sources and reference microphones on the coherence between the reference and error signals are investigated based on an analytical model. Two scenarios when the two noise sources are located on the same side or opposite sides of the error microphone are studied. The simulation results show that the coherence coefficient can reach 1.0 regardless of the distance between the noise sources and the reference microphones if the number of reference microphones is the same as that of the noise sources. When the number of reference microphones is less than that of noise sources, the coherence coefficient in the low frequency range decreases as the reference microphones move close to the noise sources.

ON NUMERICAL BEAMFORMING FOR CORRELATED DIPOLE TYPE SOURCES

A numerical beamforming method for correlated dipole-type sources in the frequency domain is developed. The typical configuration of the location of acoustic field sources and microphones is considered to analyze the noise generated under an aircraft flying in turbulent flow regimes. Three problems of numerical beamforming are studied, allowing one to take into account a priori information about connections between the components of the dipole function at a point. They differ in the number of real functions to be found: six (no connection), four (components are in phase) and two (the direction of the dipole moment is known). The discretization parameters of source function grids and microphones are estimated to ensure stable matrix inversion in numerical beamforming algorithms. The issues of nonuniqueness of solutions for the tangent components of the dipole function in the first and second problems are identified and discussed; for the third problem such an issue does not arise.

Direction-of-arrival and power spectral density estimation using a single directional microphone and group-sparse optimization

In this paper, two approaches are proposed for estimating the direction of arrival (DOA) and power spectral density (PSD) of stationary point sources by using a single, rotating, directional microphone. These approaches are based on a method previously presented by the authors, in which point source DOAs were estimated by using a broadband signal model and solving a group-sparse optimization problem, where the number of observations made by the rotating directional microphone can be lower than the number of candidate DOAs in an angular grid. The DOA estimation is followed by the estimation of the sources’ PSDs through the solution of an overdetermined least squares problem. The first approach proposed in this paper includes the use of an additional nonnegativity constraint on the residual noise term when solving the group-sparse optimization problem and is referred to as the Group Lasso Least Squares (GL-LS) approach. The second proposed approach, in addition to the new nonnegativity constraint, employs a narrowband signal model when building the linear system of equations used for formulating the group-sparse optimization problem, where the DOAs and PSDs can be jointly estimated by iterative, group-wise reweighting. This is referred to as the Group-Lasso with l_1-reweighting (GL-L1) approach. Both proposed approaches are implemented using the alternating direction method of multipliers (ADMM), and their performance is evaluated through simulations in which different setup conditions are considered, ranging from different types of model mismatch to variations in the acoustic scene and microphone directivity pattern. The results obtained show that in a scenario involving a microphone response mismatch between observed data and the signal model used, having the additional nonnegativity constraint on the residual noise can improve the DOA estimation for the case of GL-LS and the PSD estimation for the case of GL-L1. Moreover, the GL-L1 approach can present an advantage over GL-LS in terms of DOA estimation performance in scenarios with low SNR or where multiple sources are closely located to each other. Finally, it is shown that having the least squares PSD re-estimation step is beneficial in most scenarios, such that GL-LS outperformed GL-L1 in terms of PSD estimation errors.

Assessment of radio(chemo)therapy-related dysphagia in head and neck cancer patients based on cough-related acoustic features: a prospective phase II national clinical trial (ACCOUGH-P/A trial)

BackgroundRadiation-associated dysphagia is defined as impaired swallowing efficiency/safety following (chemo)radiotherapy in head and neck cancer patients. In a dysphagia framework, impaired coughing may lead to lung aspiration and fatal lung infection. Although cough efficacy is a predictor of the risk of aspiration, cough investigation is minimal in patients with radiation-associated dysphagia. Because cough is a transient signal, existing software for speech analysis are not appropriate. The goal of our project is to develop an assessment method using acoustic features related to voluntary and reflexive coughs as biomarkers of the risk of penetration/aspiration in patients with radiation-associated dysphagia.MethodsHealthy subjects and head and neck cancer patients with and without dysphagia will produce voluntary coughs, throat clearings and reflexive coughs. Recordings will be made using an acoustic microphone and a throat microphone. The recorded signals will be manually segmented and subsequently analysed with a software under development. Automatic final segmentation enables to measure cough duration. The first method of analysis includes temporal features: the amplitude contour, the sample entropy and the kurtosis. These features report respectively the strength, the unpredictability (turbulence noise due to the air jet) and the impulsive quality (burst) of the signal. The second method of analysis consists of a spectral decomposition of the relative cough signal energy into several frequency bands (0–400 Hz, 400–800 Hz, 800–1600 Hz, 1600–3200 Hz, > 3200 Hz). The primary outcome of this exploratory research project is the identification of a set of descriptive acoustic cough features in healthy subjects as reference data (ACCOUGH). The secondary outcome of this research in head and neck cancer patients with radiation-associated dysphagia includes the identification of (1) a set of descriptive acoustic cough features as biomarkers of penetration-aspiration (ACCOUGH-P/A), (2) swallowing scores, (3) voice features and (4) aerodynamic cough features.DiscussionThis study is expected to develop methods of acoustic cough analysis to enhance the assessment of radiation-associated dysphagia in head and neck cancer patients following (chemo)radiation.Trial registrationInternational Standard Randomized Controlled Trials Number (ISRCTN) registry ISRCTN16540497. Accepted on 23 June 2023.

LFM based Wideband DOA Estimation using Deep Neural Network at Low SNR

This work focuses on deep learning-based wideband direction-of-arrival (DoA) estimation for a wideband in particular LFM in case of extreme noise. We propose a convolutional neural network (CNN) that utilizes the correlation matrix to estimate and trained using multi-channel data in low SNR conditions. By using a systematic approach and treating the problem as a way to identify multiple possible DoAs, the CNN is trained to predict DoAs under different SNR conditions. This allows the CNN to accurately estimate the directions from which signals are coming, regardless of the level of noise in the environment. The architecture proposed exhibits robustness to noise, works effectively with a small number of snapshots, and achieves high resolution in angle estimation. Experimental findings demonstrate notable enhancements in performance under low SNR conditions when compared to existing methods, without the need for parameter tuning for correlated and uncorrelated sources. The enhanced robustness of our solution has broad applications in various fields, including wireless array sensors, acoustic microphones, and sonars.

A Study on the Impact of Lombard Effect on Recognition of Hindi Syllabic Units Using CNN Based Multimodal ASR Systems

Research work on the design of robust multimodal speech recognition systems making use of acoustic and visual cues, extracted using the relatively noise robust alternate speech sensors is gaining interest in recent times among the speech processing research fraternity. The primary objective of this work is to study the exclusive influence of Lombard effect on the automatic recognition of the confusable syllabic consonant-vowel units of Hindi language, as a step towards building robust multimodal ASR systems in adverse environments in the context of Indian languages which are syllabic in nature. The dataset for this work comprises the confusable 145 consonant-vowel (CV) syllabic units of Hindi language recorded simultaneously using three modalities that capture the acoustic and visual speech cues, namely normal acoustic microphone (NM), throat microphone (TM) and a camera that captures the associated lip movements. The Lombard effect is induced by feeding crowd noise into the speaker’s headphone while recording. Convolutional Neural Network (CNN) models are built to categorise the CV units based on their place of articulation (POA), manner of articulation (MOA), and vowels (under clean and Lombard conditions). For validation purpose, corresponding Hidden Markov Models (HMM) are also built and tested. Unimodal Automatic Speech Recognition (ASR) systems built using each of the three speech cues from Lombard speech show a loss in recognition of MOA and vowels while POA gets a boost in all the systems due to Lombard effect. Combining the three complimentary speech cues to build bimodal and trimodal ASR systems shows that the recognition loss due to Lombard effect for MOA and vowels reduces compared to the unimodal systems, while the POA recognition is still better due to Lombard effect. A bimodal system is proposed using only alternate acoustic and visual cues which gives a better discrimination of the place and manner of articulation than even standard ASR system. Among the multimodal ASR systems studied, the proposed trimodal system based on Lombard speech gives the best recognition accuracy of 98%, 95%, and 76% for the vowels, MOA and POA, respectively, with an average improvement of 36% over the unimodal ASR systems and 9% improvement over the bimodal ASR systems.

Highly sensitive Fabry-Perot acoustic sensor based on optic fiber spherical end surface

This paper presents and experimentally validates a highly sensitive fiber-optic Fabry-Perot interferometer sound sensor based on a fiber-optic spherical structure. The Fabry-Perot interferometer comprises an aluminum foil diaphragm and a fused fiber-optic microsphere end face, both sealed in a structure made of a glass tube. An optical fiber microsphere structure is used for the first time in acoustic sensing. Based on the strong focusing capability of the microsphere, the high coupling efficiency to the reflected beam, and the extensive range of the focused convergent optical field formed, the focused convergent optical fields facilitate the sensing of an extensive range of motion or deformation of the cavity compared to the divergent optical field of a flat fiber end face, i.e., the acoustic signals at more minor sound pressures can also be well sensed, thus compared to a flat fiber end face fiber The acoustic sensor can monitor acoustic signals over a more extensive frequency range and a larger range of acoustic pressure variations, and the output voltage signal is of a larger amplitude at the same acoustic signal, which allows the monitoring of acoustic signals at acoustic frequencies within the hearing range of the human ear. Experimental results show that the sensor shows a flat frequency response in the range of 20 Hz–20 kHz, covering all frequency components of the human ear hearing range, and the signal-to-noise ratio of the proposed acoustic sensor in the range of 20 Hz–20 kHz is greater than that of the flat fiber end-surface based acoustic sensor and the reference electroacoustic sensor, especially The sensor has the advantages of good high sensitivity, excellent linearity, wide planar response range, and simple manufacturing process. It can potentially be used as a highly sensitive, high acoustic quality fiber optic microphone in practical applications.

A Distributed Clustering Scheme for Dense Wireless Sensor Networks

Abstract: A sensor node, also known as an Alfeo (mainly in North America), is a sensor network node capable of processing, collecting sensor data, and communicating with other connected nodes in the network. Alpheus is a node, but a node is not always a point. Each sensor node has a microprocessor and some memory. In addition, each sensor node has one or more sensor devices such as acoustic sensors, microphone arrays, and video cameras, infrared, seismic or magnetic sensors. However, dead batteries in sensor nodes are difficult to replace. A typical sensor node consumes part of its energy during wireless communication. This research paper proposes to develop a well estimated distributed clustering model for dense wireless sensor network fields that provides improved performance over the existing clustering algorithm LEACH. The two robbery concepts behind the proposed system are the hierarchical distributed clustering mechanism and the threshold concept. Energy consumption is significantly reduced, which significantly extends the life of sensor nodes

Jet Flow and Noise Predictions for the Doak Laboratory Experiment

Large-eddy simulations (LESs) are performed for two isolated unheated jet flows corresponding to a Doak Laboratory experiment performed at the University of Southampton. The jet speeds studied correspond to acoustic Mach numbers of 0.6 and 0.8 as well as Reynolds numbers based on the nozzle exit diameter of about one million. The LES method is based on the compact accurately boundary-adjusting high-resolution technique (CABARET) and is implemented on graphics processing units (GPUs) to obtain 1000–1100 convective time units for statistical averaging with reasonable run times. In comparison with the previous jet LES calculations with the GPU CABARET method, the mean-flow velocity and turbulent intensity profiles are matched with the hot-wire measurements just downstream of the nozzle exit. The far-field noise spectra of the Doak jets are evaluated using two methods: the Ffowcs Williams–Hawkings approach and a reduced-order implementation of the Goldstein generalized acoustic analogy. The flow and noise results are compared with hot-wire and acoustic microphone measurements of the Doak Laboratory and critically analyzed in comparison with the NASA small hot jet acoustic rig database.

A new sixth-order Eigenmike® spherical microphone array for spatial sound field recording

A new spherical microphone array capable of up to 6-th order spatial sound field recording is described. Spherical microphone array beamforming is normally accomplished by judicially combining multiple acoustic pressure microphones appropriately mounted on the surface of a rigid sphere to form a set of orthonormal spherical harmonic modal beams or “Eigenbeams” (also referred to as Higher-Order-Ambisonics). Eigenbeamformer processing exploits the diffraction and scattering of the incident acoustic waves onto the rigid sphere. General beamformers are then created by properly combining the orthonormal Eigenbeams to form and steer a desired set of beampatterns up to the decomposition order limit. One advantage of using the modal decomposition approach to beamforming is that it is computationally compact, and results in an elegant scalable beamformer architecture. Steering beams formed by the spherical array is accomplished by a computationally simple matrix multiply. Another benefit is that beampatterns formed using spherical array processing maintain their design spatial responses independent of the steering direction. Beampatterns can also be frequency independent. In this talk, we will describe a new 64-element spherical microphone array and associated software capable of up to 6-th order performance, as well as present some real-world measurements.

Концепция создания беспилотного самоходного аппарата для работы в угольных шахтах. Часть 2

The article is a continuation of the research described in the Russian Mining Industry Journal, Issue 5 (https://doi.org/10.30686/1609-9192-2022-5-00-00). This paper presents the Pathfinder Module of the unmanned self-propelled vehicle, which was developed within the framework of the Chameleon Project. Combination of this module with the Mule Basic Module makes it possible to create an unmanned a reconnaissance unmanned self-propelled vehicle. The Pathfinder Module is designed for terrain monitoring. This module is equipped with systems to create a mathematical model of the natural environment, which enables its movement if there is no communication with the operator. The module is equipped with a video-recording complex with the recording time of at least 4 hours, a binocular telescope with at least 18x zoom, a night vision device, a thermal imager with the angular resolution not exceeding 3° (the thermal target detection range of at least 1 000 m) and directional acoustic microphones. The article describes application scenarios of the Pathfinder Module, e.g. monitoring, reconnaissance, rescue and firefighting missions in a mine. The authors believe that serial production of the Chameleon range should begin as soon as possible as part of the import substitution program with the potential to export these products not only to the developing countries, but also to the countries with a high level of technological development.

Develop and usage virtual schemes of remote acoustic laser microphones with visible and invisible waves

This article developed and investigates the operation of remote acoustic laser microphones in virtual and practical circuits. Various simulation processes were studied and mainly the circuit of an open optical transmitter and receiver were simulated. Another aspect of the work are the introduction and use of a laser in the invisible light range into the system, the essence of which is explained by not causing inconvenience to the environment. The invisible wave may be ultraviolet or infrared light ranges.

Low-cost measurement-grade microphone powered by MEMS elements and preamplifier housed in 3D printed enclosure

Acoustic measurement-grade microphones with flat frequency responses and adequate sensitivities are a necessary tool for many acousticians and vibroacoustic engineers. These microphones can often cost hundreds, if not thousands, of dollars. With the availability of microelectromechanical systems (MEMs) microphone elements and 3D printers, it is possible to construct drop-in replacements of these measurement grade microphones at the fraction of the cost. A MEMs system was designed with four elements in parallel to reduce uncorrelated noise. The system runs rail-to-rail on a 3.3VDC, Integrated Electronics Piezo-Electric (IEPE) powered preamplifier, producing a nominal sensitivity of 13 mV/Pa. The microphone body is 3D printed, and the final bill of material cost is less than 30 USD. The performance of the microphone was measured experimentally in a semi-anechoic chamber and verified by comparing the data to measurements of a commercial microphone: the PCB Piezotronics 378B02 ½” free-field microphone with a nominal sensitivity of 50 mV/Pa. This presentation will show that the MEMs microphone has a similar electrical noise floor, and lower acoustical noise floor below 1 kHz. The frequency response of the MEMs microphone is flat in the audio band through 10 kHz, making it a suitable replacement for acoustical measurements where its lower sensitivity can be tolerated.

Edge-Computing Meshed Wireless Acoustic Sensor Network for Indoor Sound Monitoring.

This work presents the design of a wireless acoustic sensor network (WASN) that monitors indoor spaces. The proposed network would enable the acquisition of valuable information on the behavior of the inhabitants of the space. This WASN has been conceived to work in any type of indoor environment, including houses, hospitals, universities or even libraries, where the tracking of people can give relevant insight, with a focus on ambient assisted living environments. The proposed WASN has several priorities and differences compared to the literature: (i) presenting a low-cost flexible sensor able to monitor wide indoor areas; (ii) balance between acoustic quality and microphone cost; and (iii) good communication between nodes to increase the connectivity coverage. A potential application of the proposed network could be the generation of a sound map of a certain location (house, university, offices, etc.) or, in the future, the acoustic detection of events, giving information about the behavior of the inhabitants of the place under study. Each node of the network comprises an omnidirectional microphone and a computation unit, which processes acoustic information locally following the edge-computing paradigm to avoid sending raw data to a cloud server, mainly for privacy and connectivity purposes. Moreover, this work explores the placement of acoustic sensors in a real scenario, following acoustic coverage criteria. The proposed network aims to encourage the use of real-time non-invasive devices to obtain behavioral and environmental information, in order to take decisions in real-time with the minimum intrusiveness in the location under study.

Design and Dynamics of Oil Filled Flexural Ultrasonic Transducers for Elevated Pressures

The flexural ultrasonic transducer has traditionally been limited to proximity measurement applications, such as car-parking systems and industrial metrology. Principally, their classical form is unsuitable for environments above atmospheric 1 bar pressure, due to an internal air cavity which creates a pressure imbalance across the transducer&#x2019;s vibrating membrane. This imbalance leads to physical deformation and degradation of the transducer&#x2019;s structure, restricting the membrane&#x2019;s capacity to vibrate at resonance to transmit and receive ultrasound. There is a requirement for ultrasonic sensors which can withstand environments of elevated pressure, for example in ultrasonic gas metering. Recent research demonstrated the dynamic performance of flexural ultrasonic transducers with vented structures, allowing the pressure to balance across the transducer membrane. However, a hermetically sealed transducer is a more practical and robust solution, where the internal components of the transducer, such as the piezoelectric ceramic disc, will be protected from harmful environmental fluids. In this research, the design and fabrication of a new form of flexural ultrasonic transducer for environments of elevated pressure is demonstrated, where the internal air cavity is filled with an incompressible fluid in the form of a non-volatile oil. Dynamic performance is measured through acoustic microphone measurements, electrical impedance analysis, and pulse-echo ultrasound measurement. Together with finite element analysis, stable ultrasound measurement is achieved above 200 bar in air, opening the possibility for reliable ultrasound measurement in hostile environments of elevated pressure.