Browse Topic: Audio equipment
Acoustic user interfaces and audio experiences are among the leading comfort factors in new vehicle interior designs. OEMs are more and more focusing on loudspeaker design and positioning, to provide the most immersive experience to the customers. The industrial target is to be able to predict the performance of an audio system in early design phases. This paper presents an integrated vibro-acoustic methodology enabling early-stage prediction of loudspeaker performance in real vehicle conditions. The approach combines electromechanical characterization, a hybrid loudspeaker calibrated model valid across the audible range and coupled FEM/BEM/SEA simulations to capture the loudspeaker response in the vehicle’s cabin considering door-installation effects and cabin acoustics. The method is validated experimentally on a rear-door loudspeaker installed in a production vehicle, showing strong correlation with measured SPL. A final application case demonstrates its capability to assess the impact of alternative speaker mounting positions during the design phase.
This paper presents a study of gunshot acoustic signal detectability in the near field of propeller noise, with a focus on the isolation of external gunshot signatures masked by propeller-induced noise. Controlled measurements were conducted in a Recirculation Delayed Anechoic Chamber (RDAC), where acoustic data were collected across varying rotor speeds, source locations, and propagation distances. Propeller noise characteristics were verified using UCD-QuietFly. The recorded signals were analyzed for the acoustic pressure, sound pressure level, and overall sound pressure level directivity to quantify masking effects. Results show that RPM is the dominant factor governing signal detectability. At 3000 RPM, the gunshot signal remains clearly identifiable within the low frequency range of 200–2000 Hz. At 4000 RPM, the signal becomes partially masked, while at 5000 RPM, propeller noise fully dominates and the gunshot signal becomes undetectable. Detectability is further reduced with increasing propagation distance. In-plane microphone locations provide improved detectability. A machine learning-based spectral separation framework was developed to suppress propeller noise and enhance the visibility of impulsive gunshot signatures in multichannel spectrograms. Experimental results show that learning-based denoising is effective at lower RPMs where the signal-to-noise ratio remains favorable, but performance degrades as broadband masking intensifies at higher rotor speeds.
Passenger expectations for quiet and acoustically comfortable vehicle interiors have increased significantly, driven by advancements in electric vehicles and premium audio systems. Acoustic comfort affects perceived quality, communication ease, and overall driving experience. This paper presents a simulation-driven methodology to predict and optimize interior noise performance during the early design phase, focusing on high-frequency acoustic transfer functions and trim material absorption properties. Traditional NVH development relies heavily on physical testing, which is time-consuming and costly. Early-stage predictive tools are essential to evaluate acoustic performance before prototype availability. High-frequency noise (1kHz–12kHz) is particularly challenging due to complex reflections and absorption behavior. Acoustic trims play a critical role in shaping the cabin’s sound field, and their properties must be optimized to achieve desired sound quality. A novel simulation approach is developed using Raytracing (Beam + Particle) to model sound propagation within the vehicle cabin. The method calculates ATFs between point sources (e.g., door panels) and receiver positions (passenger ears), enabling spatially resolved acoustic analysis. This supports early design evaluations by predicting how changes in geometry and materials affect perceived noise levels. Using HEEDS, a DOE-based optimization is performed on frequency-dependent absorption properties of acoustic trims. The trim package includes carpet, headliner, seats, doors, and firewall. The optimization targets mid-to-high frequency ranges where material behavior significantly influences sound quality. Multiple design iterations are evaluated to identify configurations that minimize intrusive noise and enhance tonal balance. A full-vehicle correlation study is conducted to validate the simulation results. Measured ATFs from a physical prototype are compared with simulated data. The acoustic trim package used in the prototype includes all major components. The Raytracing-based ATF model shows strong correlation with measured data. The methodology enables early identification of design choices that degrade or enhance acoustic comfort.
The Audio system is an important part of the design of a vehicle cabin. In the vehicle development process, the audio system needs to be tuned for optimal acoustic performance. Traditionally, this process is performed physically on vehicles. In this paper, a methodology is developed to numerically simulate the acoustic performance of the audio system across the full audible frequency range. To provide validation of the method, the p/v acoustic transfer functions (ie., the sound pressure p at the passengers’ ears divided by the voltage inputs v) are measured for different speakers in a production vehicle. As the sound perceived by the passengers depends on both the source and the path, the method development is split into two parts: (a) characterization of parameters that describe the loudspeaker as a source and (b) representation of the vehicle cabin as a path. The speaker parameters are characterized from sound radiation data measured in a 2pi chamber. To represent the vehicle cabin, a hybrid BEM-SEA model is utilized in which the cabin is fully deterministic below 1kHz and is statistical between 1 kHz and 20 kHz. The speaker model is then integrated into the cabin model in order to predict the acoustic transfer functions. This model accounts for two-way coupling between the speakers and the cabin. The results show that the predicted transfer functions are in very good agreement with the data from acoustic measurements. Therefore, performing the audio tuning virtually by numerical simulation is a feasible solution for the industry.
For music producers, engineers, and musicians, the studio is a sacred place. It's a place where creativity can be recorded and eventually shared with fans. Whether that music is being recorded in the studio or at an event, the process of properly mixing the files can be time-consuming. This is doubly true now that artists can release music mixed with Dolby's Atmos technology, a surround sound system that, among other things, takes into account the height of a speaker. This immersive technology produces music that surrounds the listener, but involves a complex backend that producers and engineers tap into from audio tools like Logic and Pro Tools. They typically do this from a professional studio filled with high-end gear and expensive speakers. Mercedes-Benz wants to give these producers and engineers the opportunity to do this work on the go via a new “Crafted in Mercedes” partnership with Dolby and the Universal Music Group.
A cooperative flight test campaign between the US Army and NASA was performed. This test sought to characterize the acoustic emissions of a fully instrumented MD530F helicopter using a snapshot array and a phased array of microphones. The snapshot array of microphones aimed to provide even coverage across the surface of a hemisphere, providing an acoustic emission hemisphere in a single 'snapshot' of time. The phased array of microphones was designed to provide enough resolution to determine noise sources from each individual blade as well as perform source separation from main rotor and tail rotor emissions. Test conditions for the characterization effort were chosen using a traditional one-factor-at-a-time approach as well as three design of experiment approaches. Characterization conditions included constant speed level flight, descent, and ascent conditions. Transient maneuver conditions were also captured over the snapshot array. The vehicle instrumentation included measurements of pilot controls, optical sensors to measure blade azimuth locations, pitch link loads, along with strain gauges to measure structural loads, blades and fuselage. This report will provide an overview of the test, document the data acquired, and provide some initial results.
Large eddy simulations (LES) of two HVAC duct configurations at different vent blade angles are performed with the GPU-accelerated low-Mach (Helmholtz) solver for comparison with aeroacoustics measurements conducted at Toyota Motor Europe facilities. The sound pressure level (SPL) at four near-field experimental microphones are predicted both directly in the simulation by recording the LES pressure time history at the microphone locations, and through the use of a frequency-domain Ffowcs Williams-Hawking (FW-H) formulation. The A-weighted 1/3 octave band delta SPL between the two vent blades angle configurations is also computed and compared to experimental data. Overall, the simulations capture the experimental trend of increased radiated noise with the rotated vent blades, and both LES and FW-H spectra show good agreement with the measurements over most of the frequency range of interest, up to 5,000Hz. For the present O(30) million cell mesh and relatively long noise data collection of 0.5s, the simulation results can be obtained in about 6 hours on 8 standard GPUs. Accurate and efficient numerical predictions of the SPL from HVAC ducts would allow automotive manufacturers to assess different duct configurations in the early design cycles and avoid the costly countermeasures necessary when excessive noise is observed in the experimental phase of the final design.
Design verification and quality control of automotive components require the analysis of the source location of ultra-short sound events, for instance the engaging event of an electromechanical clutch or the clicking noise of the aluminium frame of a passenger car seat under vibration. State-of-the-art acoustic cameras allow for a frame rate of about 100 acoustic images per second. Considering that most of the sound events introduced above can be far less than 10ms, an acoustic image generated at this rate resembles an hard-to-interpret overlay of multiple sources on the structure under test along with reflections from the surrounding test environment. This contribution introduces a novel method for visualizing impulse-like sound emissions from automotive components at 10x the frame rate of traditional acoustic cameras. A time resolution of less than 1ms eventually allows for the true localization of the initial and subsequent sound events as well as a clear separation of direct from reflected sound. The measurement instrumentation uses a rotating linear array of a few digital microphones which granularly scans the incident sound field on a circular area. The proposed method for computing an acoustic image is based on compensating the moving microphone signals for Doppler distortions and evaluating the coherence of the resulting signals with a non-moving reference microphone for each point in the acoustic image. The methodology is evaluated in the context of localizing the periodic engage event of an electromechanical clutch and the clicking noise of the aluminium frame of a passenger car seat under periodic excitation.
Automotive audio components must meet high quality expectations with ever-decreasing development costs. Predictive methods for the performance of sound systems in view of the optimal locations of loudspeakers in a car can help to overcome this challenge. Use of simulation methods would enable this process to be brought up front and get integrated in the vehicle design process. The main objective of this work is to develop a virtual auralization model of a vehicle interior with audio system. The application of inverse numerical acoustics [INA] to source detection in a speaker is discussed. The method is based on truncated singular value decomposition and acoustic transfer vectors The arrays of transfer functions between the acoustic pressure and surface normal velocity at response sites are known as acoustic transfer vectors. In addition to traditional nearfield pressure measurements, the approach can also include velocity data on the boundary surface to improve the confidence of the source identification. The surface vibration pattern over the surface of the virtual speaker is first extracted based on measured sound pressure data. The acoustic response in a free field generated by the virtual speaker is validated by comparing the sound pressure level from direct measurements and from numerical prediction. The validated virtual speaker with vibration pattern is then applied in a full vehicle model to predict interior sound field. Investigated the interior noise due to speaker with its directivity considered. Inverse numerical acoustics used to retrieve the surface normal velocities on the acoustic model. The technique allows to back calculate the operational vibrations based on operational near field pressure measurements. Near field pressure measurements are required to capture all acoustic waves (radiated waves + evanescent waves). More mid-field pressure measurements were taken to verify the correctness of the suggested method. A good agreement is discovered when the measurements are compared to the re-computed field.
Airplane manufacturers running noise tests on new aircraft now have a much cheaper option than traditional wired microphone arrays. And it’s sensitive enough to help farmers with pest problems. The wireless microphone array that one company recently created with help from NASA can locate crop-threatening insects by listening for sound they make in fields. And now, it’s making fast, affordable testing possible almost anywhere.
The transition from ICE to electric power trains in new vehicles along with the application of advanced active and passive noise reduction solutions has intensified the perception of noise sources not directly linked to the propulsion system. This includes road noise as amplified by the tire cavity resonance. This resonance mainly depends on tire geometry, gas temperature inside the tire and vehicle speed and is increasingly audible for larger wheels and heavier vehicles, as they are typical for current electrical SUV designs. Active technologies can be applied to significantly reduce narrow band tire cavity noise with low costs and minimal weight increase. Like ANC systems for ICE powertrains, they make use of the audio system in the vehicle. In this paper, a novel low-cost system for road induced tire cavity noise control (RTNC) is presented that reduces the tire cavity resonance noise inside a car cabin. The approach is cheap in terms of computational effort (likewise ICE order cancellation) as well as additional hardware components. The signal from only one single-axis-accelerometer is used to estimate the frequency of the tire cavity resonance in real time. The sensor position is chosen to achieve a high signal to noise ratio (SNR) for the resonance which leads to a robust frequency estimation but does not require specific high coherence with interior noise components. The interior microphones and speakers of the vehicle are used to control the narrow-band noise at the estimated frequency. The performance of the system is investigated based on the simulation results as well as measurements in a real vehicle. The results match well and demonstrate that the technology is well understood, allowing potential virtual system tuning based on reliable simulation data. The system shows a high global reduction of the cavity noise in the vehicle’s interior.
When traveling in an open-jet wind tunnel, the path of an acoustic wave is affected by the flow causing a shift of source positions in acoustical maps of phased arrays outside the flow. The well-known approach of Amiet attempts to correct for this effect by computing travel times between microphones and map points based on the assumption that the boundary layer of the flow, the so-called shear layer, is infinitely thin and refracts the acoustical ray in a conceptually analogy to optics. However, in reality, the turbulent nature of both the not-so-thin shear layer and the acoustic emission process itself causes an additional smearing of sources in acoustic maps, which in turn causes deconvolution methods based on these maps – the most prominent example being CLEAN-SC – to produce certain ring effects, so-called halos, around sources. In this paper, we intend to cast some light on this effect by describing our path of analyzing/circumventing these halos and how they are linked to the CLEAN algorithm itself. Moreover, we outline a methodological extension to CLEAN-SC, which comes at a reasonable computational cost but effectively eliminates this effect in real-world measurements.
This paper describes a mathematical framework for determining the optimal sensor set location for adequately capturing the sound generated by rotors. The approach leverages the gappy-POD method proposed by Everson and Sirovich [J. Opt. Soc. Am., Vol. 12, 1995, pp. 1657-1664], which first identifies the various mode constituents that make up the first few rotor blade-pass frequency harmonics of the sound-field. The algorithm is developed using a covariance matrix for the POD problem comprising auto- and cross-spectral densities of spatially and temporally resolved sound waves captured by an array of microphones oriented parallel to the axis of a laboratory-scale hovering rotor. Three different forms of the technique are developed and compared. These comprise a homogeneous form and two heterogeneous forms; the heterogeneous forms are referred to as XX-topos and XX-chronos and depends on which term in the error minimization equation is assigned the gappy sensor set. A greedy algorithm is then employed to determine the optimal location of the limited sensor set. The findings are analyzed for different combinations of POD modes and blade-pass frequency harmonics of the sound generated by the hovering rotor.
A pair of earbuds can be turned into a tool to record the electrical activity of the brain as well as levels of lactate in the body with the addition of two flexible sensors screen-printed onto a stamp-like flexible surface.
While there is a tendency for new vehicles to have a focus on ride, handling, performance and other dynamic elements, the model year 2024 Lincoln Nautilus team added another element to how the driver will experience the midsize SUV. Not that the ride, handling, etc. were ignored, but the global design and engineering team wanted to do something different with this two-row SUV. Recognize that this is a vehicle with a sumptuous interior that includes not only first-class seating (24-way adjustable front seats) and materials (Alpine Venetian leather available on the seats; cashmere for the headliner) but also an available high-end Revel Ultima 3D audio system with 28 speakers. What's more, there's “Lincoln Digital Scent,” small electronically activated pods containing various aromas (e.g., Mystic Forest, Ozonic Azure, Violet Cashmere). Across the top of the instrument panel there is a 48-inch backlit LCD screen and a 11.1-inch touchscreen in the center stack.
Smart accessories are increasingly common. Rings and watches track vitals, while Ray-Bans now come with cameras and microphones. Wearable tech has even broached brooches. Yet certain accessories have yet to get the smart touch.
Pass-by noise measurement is mandatory for automotive manufacturers for conformity of production. With evolving of pass-by noise requirements (under 68 dB in 2024), all the stakeholders should be able to comply with this criterion. OEMs, suppliers of passive acoustic treatments, road manufacturers and tire manufacturers are concerned and should deploy efforts to provide solutions for control of exterior noise. In this regard, simulations are preferable over measurement campaigns as they can provide fast feedback on passive exterior treatments for exterior noise control. In the particular case of Lightyear vehicles, the main contributors to pass-by noise are tires and in-wheel motors. Considering that, a contribution of each of these two sources of noise to pass-by noise will be described. Tire noise sources and motor noise sources will be replaced by simple monopole sources. The best monopole source location for both tires and motors is discussed. Actran vibro-acoustic Finite Element software is used to predict the noise at pass-by microphones. The calculation process takes advantage of advanced techniques to optimize the process. The acoustic transfer functions (TFs) from monopole sources to microphones are calculated first. The TFs are computed in different conditions considering acoustic treatments in different areas. Finally, these transfer functions are recombined with source strengths from tire and motor monopole sources. The pass-by noise simulation results are compared to the pass-by noise test results to conclude on the simulation accurateness.
The implementation of enablers on a luxury sport utility vehicle is used to illustrate the development process for reduction of road noise. The vehicle in this case study was launched into production with two tuned mass dampers for reduction of low frequency road noise content which was amplified by frame modes. Additionally, resonators were integrated into the wheels (rims) to address the dominant cavity resonance frequencies. The results of this successful production implementation are illustrated herein. An RNC (road noise cancellation) system was integrated into the case vehicle to assess its performance relative to the passive enablers listed above. This production representative (embedded software solution) RNC system utilized the vehicle’s existing audio system for creation of active noise to cancel noise content which was predicted using accelerometers mounted to the vehicle chassis. A comparison of in-vehicle noise indicated a significant reduction at low frequencies (at all seating locations) when utilizing the active noise control solution. These noise improvements are coupled with a vehicle mass reduction of greater than 4 kg, when compared to the passive enabler solution.
This contribution describes a novel method for visualizing leakages in automotive structures using a rotating linear array of a few digital ultrasound microphones in combination with a multi-frequency ultrasound transmitter. The rotating array scans the incident sound field generated by the ultrasound transmitter on a circular area. In a typical measurement setup, the ultrasound transmitter is placed in a cavity (e.g. car interior, trunk or similar) and operates at distinct harmonic frequencies at around 40kHz in an omnidirectional fashion. The rotating linear array is operated on the outside of the cavity and captures the sound field escaping through small leakages. While the reduced hardware complexity allows for the design of a lightweight, handheld sound imaging device, the algorithmic portion of the measurement system requires special attention. In fact, established methods of sound imaging like beamforming and nearfield holography cannot be applied to signals stemming from moving sensors. The proposed method of computing an acoustic image using the described measurement setup is based on compensating the moving microphone signals for Doppler distortions and evaluating the coherence of the resulting signals with a non-moving reference microphone for each point in the acoustic image. The setup and methodology is evaluated for leakage and tightness testing of actual automotive components and structures for production cars in a quality control context. The corresponding troubleshooting process from assessment and quantification of the situation to resolution of the root cause is described from a user perspective.
Speaker performance in Acoustic Vehicle Alerting System (AVAS) plays a crucial role for pedestrian safety. Sound radiation from AVAS speaker has obvious directivity pattern. Considering this feature is critical for accurately simulating the exterior sound field of electrical vehicles. This paper proposes a new process to characterize the sound directivity pattern of AVAS speaker. The first step of the process is to perform an acoustic testing to measure the sound pressure radiated from the speaker at a certain number of microphone locations in a free field environment. Based on the geometry of a virtual speaker, the locations of each microphone and measured sound pressure data, an inverse method, namely the inverse pellicular analysis, is adopted to recover a set of vibration pattern of the virtual speaker surface. The recovered surface vibration pattern can then be incorporated in the full vehicle numerical model as an excitation for simulating the exterior sound field. In this study, the process is illustrated in detail and validated with a production AVAS speaker. Using the virtual speaker and the extracted vibration information, the sound pressure level (SPL) at each microphone location is numerically calculated. The SPL from the direct measurement and the prediction matches very well. By using the virtual speaker and its surface vibration, the directivity pattern of its sound field is fully recovered. Furthermore, numerical analysis is performed to calculate the sound field of the AVAS speaker in a full vehicle model. The acoustic transfer functions from the speaker location to three regulatory microphone locations are calculated. Results clearly reveal the deficiency of using a monopole to represent AVAS speaker and the necessity to consider its directivity pattern.
To empirically estimate the radiation of sound sources, a measurement with microphone arrays is required. These are used to solve an inverse problem that provides the radiation characteristics of the source. The resolution of this estimation is a function of the number of microphones used and their position due to spatial aliasing. To improve the radiation resolution for the same number of microphones compared to standard methods (Ridge and Lasso), a method based on normalizing flows is proposed that uses neural networks to learn empirical priors from the radiation data. The method then uses these learned priors to regularize the inverse source identification problem. The effects of different microphone arrays on the accuracy of the method is simulated in order to verify how much additional resolution can be obtained with the additional prior information.
In the late 1970’s and early 1980’s, Jing-Yau Chung along with Joseph Pope published several external General Motors reports on the then novel measurement of sound intensity (SI) using the two-microphone, cross-spectral method. Application of this measurement method was then extended to sound intensity measurements in flow. Through component wind tunnel measurements, it was determined that the intensity of noise sources could be accurately measured up to a level of 15 dB below the sound pressure level generated by flow noise on microphones. An initial application of this method was to the identification of noise sources alongside rolling truck tires. It was then extended to the measurement of the aerodynamic noise generated by protrusions added to automotive vehicle designs. These included items such as outside rearview mirrors, windshield wipers, A-pillar offsets, grille whistles, roof racks, underbodies, and fixed-mast radio antennas. Many of these could be applied on the early full-size clay models or other mock-ups as well as actual vehicles. An application of sound intensity was the development of the straked antenna design leading to a GM Defensive Patent and its now universal application to virtually all vehicles with simple fixed-mast antennas. The development of this design is highlighted along with the background on the application of sound intensity to measurements in air flow.
When an emergency vehicle is approaching but its blaring siren isn't heard by nearby motorists, all are at risk. Engineers at Harman International have developed novel sensor technology that detects both the sound and its direction, in effect piping that screaming siren into vehicles so-equipped, to alert the driver. “What we're in essence doing is turning the vehicle into a giant microphone,” Mitul Jhala, senior director of automotive embedded audio for Harman, explained in an SAE Media interview.
A new auditory sensor will be useful for healthcare devices that diagnose respiratory diseases. The skin-attachable device will also be useful as a sensor in microphones to aid in facilitating communication in disaster situations. It can clearly detect voices even in harsh noisy environments.
Experimental procedures are developed for the measurement and characterization of noise from small multirotor aircraft. These procedures are applied to measure the noise of the Tarot X8. The acoustic characteristics of the Tarot X8 are evaluated for a number of level flight flyover conditions. Both tonal and broadband noise is found to be significant, but the relative importance depends on the angle of observation. Variability in noise is assessed both across repeated runs of the same condition and within a run using an array of microphones parallel to the flight track. Variability is found to increase as the distance between the microphone and aircraft increases. Variations within a run are significant (on the order of 2 dBA), but do not explain the greater variation (on the order of 5 dBA) in levels between runs.
Smart speakers have proven adept at monitoring certain healthcare issues at home including detecting cardiac arrest or monitoring babies’ breathing. Now, the speakers can be used to track the minute motion of individual heartbeats in a person sitting in front of the speaker.
Technology for automotive active noise cancellation (ANC) such as HARMAN’s Engine Order Cancellation (EOC) system help reduce in-cabin noise levels using a set of error microphones and the vehicle’s built-in audio system to generate anti-noise signals. A major benefit of these systems is that significant reduction in unwanted noise levels in the 20 - 400 Hz range can be achieved without the addition of extra noise control material. However, in the instances where the frequencies of anti-noise signals and music signals overlap, a degradation in the overall music reproduction quality is possible. In this paper, we study the effects of EOC on music playback by applying signal processing and statistical methods to objectively measure degradation in audio content when EOC is active. This study is carried out using production EOC software in a simulation environment. The simulation models the cabin acoustic response from measured vehicles and uses recordings of vehicle noise and music as inputs. For each test case, we simulate in-cabin music playback in the presence of engine noise with and without EOC active. This analysis is performed on a large set of music spanning various genres to maximize the likelihood of matching the listening preferences of our end-users. Finally, we also show that musical interference suppression (MIS) algorithms such as TrueAudio can reduce degradation in music reproduction quality when the frequencies of ANC anti-noise signals and music overlap.
This paper presents experimental investigations of determining and analyzing low-frequency, low-SNR (Signal to Noise Ratio) noise sources of an automobile by using a new technology known as Sound Viewer. Such a task is typically very difficult to do especially at low or even negative SNR. The underlying principles behind the Sound Viewer technology consists of a passive SODAR (Sonic Detection And Ranging) and HELS (Helmholtz Equation Least Squares) method. The former enables one to determine the precise locations of multiple sound sources in 3D space simultaneously over the entire frequency range consistent with a measurement microphone in non-ideal environment, where there are random background noise and unknown interfering signals. The latter enables one to reconstruct all acoustic quantities such as the acoustic pressure, acoustic intensity, time-averaged acoustic power, radiation patterns, etc. By combining a passive SODAR and modified HELS methods, engineers will be able to visualize all acoustic quantities. In particular, Sound Viewer enables engineers to extract target information with a negative SNR, for example, SNR < - 30 dB, and identify the precise locations of very low frequency (< 200 Hz) airborne and structure-borne sound sources with very high spatial resolution. Test results of Sound Viewer to analyze the engine sparkplug and muffler noise of an automobile sedan are presented.
Ear infections occur when fluid builds up in the middle ear behind the eardrum and is infected. This buildup is also common in another condition called otitis media with effusion. Any kind of fluid buildup can be painful and make it hard for children to hear. A new smartphone app can detect fluid behind the eardrum by simply using a piece of paper and a smartphone’s microphone and speaker.
The extreme low-frequency infrasonic hydrophone, with associated software, is capable of sensing down to .0001 Hz — a 4.999-Hz improvement from current similar systems. This ultra-low-power-consuming hydrophone also isolates and removes significant amounts of background noise inherent to the electret-type microphone not previously introduced into hydrophone applications.
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