Sound Properties Research Articles

Application of microwave holographic subsurface technology for non-destructive testing of reinforced polyurethane foam

Glass fiber Reinforced Polyurethane Foam (RPUF) has found wide application primarily in the aerospace and construction industry due to its outstanding properties. Unlike pure non-reinforced Polyurethane Foam (PUF), it has increased strength characteristics and at the same time retains unique heat and sound insulation properties. The paper considers the features of reinforced polyurethane foam examination in the Microwave (MW) range. It is shown that there is a significant difference in the recorded MW images compared to pure polyurethane foam. This is expressed primarily in the fact that the reinforcing fibers have a dielectric constant that is different from enclosing polyurethane foam, which leads to scattering and reflection of the incident electromagnetic wave on them. Experimental studies have shown that for RPUF, in contrast to PUF, there is an optimal wavelength range in which the contrast of defects against the background of glass fiber reflections is of the greatest value. An experimental comparison of two methods of examination back-scattering and forward-scattering methods was also carried out for RPUF. It is shown that the forward-scattering technology of measurements, if it can be implemented, has certain advantages since allows reducing the contrast of background reflections from the reinforcing fibers.

Auditory distraction of vocal-motor behaviour by different components of song: testing an interference-by-process account

ABSTRACT The process-oriented account of auditory distraction suggests that task-disruption is a consequence of the joint action of task- and sound-related processes. Here, four experiments put this view to the test by examining the extent to which to-be-ignored melodies (with or without lyrics) influence vocal-motor processing. Using song retrieval tasks (i.e., reproduction of melodies or lyrics from long-term memory), the results revealed a pattern of disruption that was consistent with an interference-by-process view: disruption depended jointly on the nature of the vocal-motor retrieval (e.g., melody retrieval via humming vs. spoken lyrics) and the characteristics of the sound (whether it contained lyrics and was familiar to the participants). Furthermore, the sound properties, influential in disrupting song reproduction, were not influential for disrupting visual-verbal short-term memory—a task that is arguably underpinned by non-semantic vocal-motor planning processes. Generally, these results cohere better with the process-oriented view, in comparison with competing accounts (e.g., interference-by-content).

Reflections on Archaeomusicological Practice in South America

This paper aims to describe some problems and issues that have emerged from the practice of archaeomusicology in South America, especially in the Andean region. Some methodological approaches emerge from the specific problems of organological studies of pre-Hispanic objects, related to the evidence about sound use and the interpretation of sound by local cultures. This article presents four features of Andean music that illustrate some of the main methodological approaches that must be utilized when studying pre-Hispanic music in the Andes; the tone quality, the organological expansion from a singular object to multiple objects; the physical movement of musician and hearer as part of the sound properties, and musical performance as part of a social exchange between musicians and listeners. Each of these features offers a new perspective on archaeo-musicological studies, as well as on the contributions of the field to a greater understanding of new discussions in present society. The focus of this article will be to understand the ‘sound object’ as an acoustic object, as one or more objects, as related to the surrounding ambient, as a moving object, and as a modifier of the player’s or listener’s experience.

Evaluating emotionalizing effects of active sound designs

Numerous results in the field of musicological research and traffic psychology research show that emotions can be altered by certain sets of pitches or sound characteristics, and emotions on the other hand influence our driving behaviour. Regardless, there is no research on how different artificial vehicle sounds could influence the driving behaviour via emotions. We want to create an active sound design that can alter the driver's emotions to increase traffic safety in certain driving scenarios. To evaluate which harmonic compositions and sound characteristics could be used as stimuli, we first extracted sound characteristics from different music pieces or sounds that have a proven emotionalizing effect, and generated new sounds based on said characteristics that also could work in the context of an active sound design for electrical vehicles. With these sounds, we conducted a subject study with 45 participants to evaluate if people perceive the intended emotions, and further determine the best sounds to use in future subject studies to evaluate their impact on drivers' behaviour. This paper describes the extracted sounds, their characteristics and psychoacoustical properties. Furthermore, it discusses the correlation between the sound properties and the perception of and emotional effect on the subjects.

A lightweight and transparent acoustic metamaterial sheet with designed structures for sound insulation applications

Normal sound insulation materials such as metal plates and rubber sheets follow the mass law. According to the mass law, a weight increase of sound insulators leads to high sound insulation. Therefore, novel lightweight and high-performance materials have been required in various fields such as mobility and electronics. We developed lightweight and transparent acoustic metamaterial sheets having blocklike weights with rodlike or cylindrical shapes periodically arranged on thin films. Upon sound incidence at a target frequency, the heavier weights and the lighter film cooperatively vibrate in opposite phase and with the same amplitude. The transmitted sound waves through those parts cancel each other out owing to the wave interference. As a result, the acoustic metamaterial sheets show high sound insulation performance beyond the mass law limit at the target frequencies. In this study, we report the structural design, sound insulation properties and mechanisms, and application of acoustic metamaterial sheets.

Numerical study on the sound insulation potential of the ventilating double-leaf facades

Double-leaf facades can be designed to allow natural ventilation while providing adequate sound insulation. The key concept is based on the displacement of the opening in the second layer relative to the opening in the first layer, resulting in a significant improvement in sound insulation compared to a direct opening. This sound insulation can be further improved if the sound absorption in the cavity of the double facade is increased. An extensive laboratory study was conducted to investigate the impact of different variables of such a system (e.g., the size of the openings, the location of the openings, the relative displacement of the openings in the two layers, the sound absorption in the cavity, the location of the sound absorption panels, etc.) using an experimental modular double wall. Empirical prediction models have been developed to predict the sound transmission through such double leaf facades with open elements. Their prediction is validated by measured data. In this paper, we analyze different scenarios of double leaf facades in building-scale dimensions and we use empirical models to calculate their sound insulation. This offers an insight into the sound insulation properties of a potential real-building double facade.

Sound Absorption and Material Properties of Asphalt Rubber Concrete Specimens

The acoustic and material properties of asphalt crumb rubber (ARC) pavement have been measured and correlated. Laboratory measurements revealed nonlinear relationships between the sound absorption coefficients and material properties of compacted specimens as a function of the percentage of crumb rubber content in conventional and modified binders. The acoustic performance of conventional asphalt and asphalt rubber concrete specimens are compared to their material properties as a function of crumb rubber content to determine how crumb rubber content influences sound absorption. The normal incidence sound absorption coefficients, porosity, percentage of voids in mineral aggregate, and absolute gas permeability are measured for specimens containing 0, 5, 10, 15, and 20% crumb rubber in the asphalt binder. The random incidence sound absorption coefficient and material property data share nonlinear distributions within some frequency ranges, as a function of crumb rubber content in the conventional and modified asphalt binders.

Sound insulation enhancement of PVB film by additive engineering

In recent years, noise pollution has become a prominent topic in the energy field. The lightweight and high sound insulation materials have attracted more and more attentions. This study focuses on improving the sound insulation properties of PVB films by adding a little water during the processing. When the water content was 4 %, the average sound transmission loss improved by 5.7 dB at 500–1100 Hz, with a maximum improvement of 17.6 dB, due to porous structure formed by the water additives. Meanwhile, the tensile stress was 28.1 MPa and the elongation at break achieved 140.4 %, which were 1.06 and 1.24 times higher than that of PVB without water, respectively. The porous structure and sound insulation mechanism for PVB films were characterized by SEM, BET and acoustic impedance tubes, etc. .1

Malaysian cough sound analysis and COVID-19 classification with deep learning

The use of cough sounds as a diagnostic tool for various respiratory illnesses, including COVID-19, has gained significant attention in recent years. Artificial intelligence (AI) has been employed in cough sound analysis to provide a quick and convenient pre-screening tool for COVID-19 detection. However, few works have employed segmentation to standardize cough sounds, and most models are trained datasets from a single source. In this paper, a deep learning framework is proposed that uses the Mini VGGNet model and segmentation methods for COVID-19 detection using cough sounds. In addition, data augmentation was studied to investigate the effects on model performance when applied to individual cough sounds. The framework includes both single and cross-dataset model training and testing, using data from the University of Cambridge, Coswara project, and National Institute of Health (NIH) Malaysia. Results demonstrate that the use of segmented cough sounds significantly improves the performance of trained models. In addition, findings suggest that using data augmentation on individual cough sounds does not show any improvement towards the performance of the model. The proposed framework achieved an optimum test accuracy of 0.921, 0.973 AUC, 0.910 precision, and 0.910 recall, for a model trained on a combination of the three datasets using non-augmented data. The findings of this study highlight the importance of segmentation and the use of diverse datasets for AI-based COVID-19 detection through cough sounds. Furthermore, the proposed framework provides a foundation for extending the use of deep learning in detecting other pulmonary diseases and studying the signal properties of cough sounds from various respiratory illnesses.

Self-care nursing assessment: cross-cultural adaptation and validation of the Spanish version of the Self-care of chronic illness inventory

BackgroundSelf‐care is the primary means of caring for a chronic condition. Therefore, it is necessary to assess it by using a good validity and reliability instrument. The Self-Care of Chronic Illness Inventory (SC-CII) is a generic instrument developed to measure self-care processes behaviors using three separate scales in patients with chronic illness. The original cross-cultural assessment concluded the need for future studies sampling patients from different sites to increase the generalizability of the psychometric evaluation results. It was unclear whether this tool had sound psychometrics properties in the context of Spanish culture. The purpose of this study was to cross-culturally adapt the SC-CII, test its psychometric properties and validate its use among Spanish people with chronic diseases.MethodsA cross-cultural translation of the SC-CII was performed from English to Spanish. The psychometric evaluation was conducted in a sample of 350 patients with chronic conditions through a multicenter cross-sectional study based on the STROBE guideline. Data were collected from face-to-face interviews during 2022. Internal validity was assessed with Confirmatory Factor Analysis, internal consistency reliability with Cronbach alpha for unidimensional scales and McDonald's Omega reliability coefficient for multidimensional scales.ResultsMost (63.4%) participants were older adults aged 65 years or older with a mean age of 65.45 ± 14.97. The average number of chronic conditions reported was 2.81%; the most common conditions were hypertension (52.3%), musculoskeletal disorders (46.3%) and diabetes (38.9%). Patients reported adequate self-care behaviors in all three scales of the SC-CII. The Self-Care Maintenance and Management scales were multidimensional, and the Self-Care Monitoring scale was unidimensional. In Confirmatory Factor Analysis, the Self-Care Maintenance and Monitoring scales had satisfactory fit indices. The Self-care Management scale had acceptable fit indices. The Omega reliability coefficient for multidimensional scales was 0.75 (Self-Care Maintenance) and 0.72 (Self-Care Management). The Cronbach alpha coefficient of the Self-Care Monitoring scale was 0.85. Item-total correlations were all significant except one. Test–retest reliability showed an intraclass correlation coefficient of 0.92.ConclusionsThe SC-CII has appropriate psychometrics characteristics and is a culturally suitable and reliable instrument for assessing to the self-care behaviors of patients with chronic disease in Spain. The scale provides a simple and rapid solution to assess the self-care process.

The Nature of Timbre

Along with pitch and loudness, timbre is commonly described as an audible property of sounds. This paper puts forward an alternative view—that timbres are properties of auditory media. This approach has many advantages. First, it accounts for the frequent attribution of timbres to objects that do not have characteristic sounds. Second, it explains why timbres are attributed not only to ordinary objects, like musical instruments, but also to surrounding spaces and architectural structures. And finally, it provides an original solution to the timbre-constancy problem.

Sound field recovery based on numerical data-driven and equivalent source method

Sparse representation has been applied to realize an accurate description of the sound field from limited set of measurements. The prerequisite of this application is that sound field can be sparsely represented in a specific basis. However, most of the sparse bases are constructed by using the physical models of sound field, and are only effective for a specific category of sound sources. In this paper, the data-driven dictionary learning approach is exploited to obtain a sparse basis of sound field. Meanwhile, to reduce the difficulty and workload of the collection of data sample, the equivalent source method is utilized to collect data samples by means of simulations and thus the data samples can be generated by taking advantage of sound field properties. The performance of the sound field recovery with sparse sampling based on learned dictionary is examined and is compared with those based on other sparse bases. The result indicates that numerical data-driven model is more flexible and is not limited to a specific category of sound sources. The advantage of the proposal is presented by the results of numerical simulation and experiment.

Acoustic transmission loss in Hilbert fractal metamaterials

Acoustic metamaterials are increasingly being considered as a viable technology for sound insulation. Fractal patterns constitute a potentially groundbreaking architecture for acoustic metamaterials. We describe in this work the behaviour of the transmission loss of Hilbert fractal metamaterials used for sound control purposes. The transmission loss of 3D printed metamaterials with Hilbert fractal patterns related to configurations from the zeroth to the fourth order is investigated here using impedance tube tests and Finite Element models. We evaluate, in particular, the impact of the equivalent porosity and the relative size of the cavity of the fractal pattern versus the overall dimensions of the metamaterial unit. We also provide an analytical formulation that relates the acoustic cavity resonances in the fractal patterns and the frequencies associated with the maxima of the transmission losses, providing opportunities to tune the sound insulation properties through control of the fractal architecture.

Optimization Objective Function Corona Discharge Acoustic Using Fuzzy c-Means (FcM )

In many electrical networks in Indonesia, insulation failure due to high voltage phenomena like Corona Discharge (CD) still happens. This is a result of our inability to perform early Corona Discharge (CD) identification. This study’s objective is to optimalize the sound properties of Corona Discharge (CD) as a first step throught the early identification of insulation failure in the form of clustering 20 kV cubicle. Based on observations on the needle-rod electrode 3 cm apart, the smallest breakdown was obtained at 34.3 kV. So that the classification of CD sound by 3 clusters starting 20 kV cubicle voltage until before the failure occurs on 33 kV. The temperature in the cubical is between 27.5℃ - 35.3℃ and humidity ranges from 70% - 95%. It was stated in the study that the FcM method was the most widely used and successful method. In this case, FcM can obtain more flexible results that classify data into clusters easily. This research will be carried out using the Fuzzy c-Means (FcM) method. Feature extraction with linear predictive coding (LPC) method, then optimization by using the Fuzzy c-Means (FcM) method which is expected to be used as an initial step for early detection of insulation failure.

The acoustic streaming effects and transmission mechanisms of a micro-cavity acoustic black hole structure with an abrupt cross-section

This paper investigates the acoustic streaming effects (ASEs) and mechanisms behind the transmittance of sound in a metallic micro-cavity acoustic black hole (ABH) structure with an abrupt cross-section and examines the sound field flow characteristics inside the micro-cavity ABH under the sound excitation, such as the velocity, acceleration and pressure fields. And the sound transmission mechanisms are characterized by the ASEs which can be obtained by solving Navier–Stokes equations. The numerical results show that the sharp increase in the velocity and acceleration at the ABH tip position is the main reason for the focusing of the sound energy. And the dramatic increase in the tip cross-section reduces the acoustic streaming velocity, which is the main reason for the attenuation of the sound energy. Additionally, the thermoviscous effect of the acoustic boundary layer can also dissipate the low-frequency sound energy. The sound insulation experiment shows that the proposed micro-cavity ABH structure has a sound transmission loss (STL) of over 15[Formula: see text]dB in the low-frequency regime. This research reveals the mechanisms of the ASE’s work on the sound transmission properties of the micro-cavity ABH and provides new insight into low-frequency sound wave suppression. The ABH structure proposed in this paper has excellent strength, bearing capacity and long lifecycle, so it can be applied in the construction industry through its integrated design of structure and performance.

Polyimide/SiO2 composite aerogels with excellent thermal and sound insulation properties prepared by confined filling method

Aerogels have enormous potential in integrated thermal insulation and noise reduction applications. According to the knowledge of the favorable mechanical and acoustic properties of honeycomb structures. We employed anisotropic “honeycomb-like” polyimide (PI) aerogels as the matrix and utilized a confined filling strategy to directionally filled continuous SiO2 aerogels into the PI aerogel matrix. This resulted in the creation of an exceptional organic–inorganic composite aerogel (PISis) with outstanding thermal and acoustic insulation performance. The radial thermal conductivity of PISis ranged from 22.37 to 27.65 mW·m−1·K−1, and the initial decomposition temperature was approximately 524–557 °C. In the frequency range of 500–6300 Hz, the average sound transmission loss (STL) of the 18 mm thick composite material reached 30.67 ∼ 31.89 dB, and the compressive strength at 10 % strain is 0.416 MPa. The PISis exhibits a density ranging from 0.1012 to 0.1302 g/cm3. These make it an ideal lightweight, high-strength, and efficient material for thermal and acoustic insulation.

Experimental study on the sound transmission loss suite at the University of Technology Sydney

Sound transmission loss suites are essential testing facilities for measuring the sound insulation properties of building elements and assessing noise attenuation. However, inconsistencies in test results can arise due to variations in the size, shape, and construction of test rooms across different laboratories, with biases introduced by the room acoustics or acoustical environment of the facility itself. To evaluate the reliability of such testing, we conducted an experimental study on the sound transmission loss suite at the University of Technology Sydney. Our investigation focused on three key factors: estimating the maximum achievable sound reduction using a heavyweight wall installed at the test aperture on the source room side, testing the effectiveness of vibration isolation between reverberation rooms, and assessing the decoupling of the sound field within the reverberation rooms.

Directivity and sound power of rockets: A comparative analysis of source characteristics and their implementation into a predictive model

Fundamental jet and rocket noise modeling includes quantifying the acoustic power and directivity characteristics of the source. While many attempts have been made to define a model for the sound power and directivity of jets and rockets, many of these models have been based on flawed measurements or methodologies. This paper presents the directivity and sound power characteristics as obtained from launched rockets. The results are compared with those in the literature. The directivity and sound power properties are used in a standard source model for rocket noise, and the resulting predictions are evaluated.

Analysis of sound emissions and physical properties of bubbles generated by breaking waves

Although the relationship between bubble diameter and the corresponding resonant frequency has been known since 1930s, the link between the amplitude of the sound and the physical properties of the bubble is still unclear. Sound amplitude is a parameter inevitably measured when passive acoustic measuring techniques are employed, and its magnitude as measured is related to not only the size of the bubble but also its position in space relative to the measurement point. Here, we present a study where individual bubbles were first generated through a vertical plunging jet and analyzed to establish a link between their diameters and sound emissions. Subsequently, these data were used to predict bubble properties occurring in breaking waves generated in laboratory experiments. A high frequency camera was used to capture images of the bubbles and visually check the accuracy of the diameter and location predictions. Results show good agreement between plunging jet and breaking waves bubbles within the +− 1.5 dB confidence interval; addressing with residual experimental uncertainties should offer further improvements.

Digital Filtering Techniques Using Fuzzy-Rules Based Logic Control.

This paper discusses current formulations based on fuzzy-logic control concepts as applied to the removal of impulsive noise from digital images. We also discuss the various principles related to fuzzy-ruled based logic control techniques, aiming at preserving edges and digital image details efficiently. Detailed descriptions of a number of formulations for recently developed fuzzy-rule logic controlled filters are provided, highlighting the merit of each filter. Fuzzy-rule based filtering algorithms may be designed assuming the tailoring of specific functional sub-modules: (a) logical controlled variable selection, (b) the consideration of different methods for the generation of fuzzy rules and membership functions, (c) the integration of the logical rules for detecting and filtering impulse noise from digital images. More specifically, we discuss impulse noise models and window-based filtering using fuzzy inference based on vector directional filters as associated with the filtering of RGB color images and then explain how fuzzy vector fields can be generated using standard operations on fuzzy sets taking into consideration fixed or random valued impulse noise and fuzzy vector partitioning. We also discuss how fuzzy cellular automata may be used for noise removal by adopting a Moore neighbourhood architecture. We also explain the potential merits of adopting a fuzzy rule based deep learning ensemble classifier which is composed of a convolutional neural network (CNN), a recurrent neural networks (RNN), a long short term memory neural network (LSTM) and a gated recurrent unit (GRU) approaches, all within a fuzzy min-max (FMM) ensemble. Fuzzy non-local mean filter approaches are also considered. A comparison of various performance metrics for conventional and fuzzy logic based filters as well as deep learning filters is provided. The algorhitms discussed have the following advantageous properties: high quality of edge preservation, high quality of spatial noise suppression capability especially for complex images, sound properties of noise removal (in cases when both mixed additive and impulse noise are present), and very fast computational implementation.