Acoustics Australia最新文献

This article presents the acoustic characterization of two well-known Hemadpanti-style Indian Hindu temples in Maharashtra, India, built during the twelfth century. The studies of architectural acoustics in Indian Hindu temples are sparse. Therefore, characterizing the acoustic nature of such historical Hindu temples is vital. This study may provide insight into the role of architectural characteristics that support the desired sound field, ensuring that the music ritual, singing of devotional songs, and Vedic chanting are suitable in Hemadpanti-style Hindu temples. The research aimed to report and investigate the acoustic behavior of the Hindu temples through in-situ measurements in an unoccupied condition. Virtual acoustic models were developed and validated using the in-situ measurements under the same conditions. Objective room acoustic indicators considered are reverberation time (T30), clarity of music (C80), and Speech Transmission Index (STI), which are later simulated and analyzed for two sound source positions in occupied conditions. The results report that the spatially and spectrally unoccupied averaged values for reverberation time (T30) and clarity of music (C80) of the Markanda temple are 0.98 s and 3.98 dB, and the Mrikunda temple (T30) and (C80) values are 0.73 s and 5.62 dB respectively. The values obtained for both temples are within the optimum range adopted for this study. The average subjective rating for speech intelligibility of the Markanda and the Mrikunda temples is “good”. After analyzing indicators, the results emphasize the influence of architectural features on the acoustic characteristics of the Hemadpanti style of Hindu temples.

This paper presents a generalized algorithm called the sub-cross-spectral matrix (SCSM) beamforming technique for the virtual augmentation of an N-channel beamforming array based on sequential computation of the cross-spectral matrix (CSM) terms for localizing stationary signal sources. To this end, first, the diagonal sub-cross-spectral matrices (SCSMs) of the N-channel array pertaining to M different spatial locations were obtained. Next, the off-diagonal SCSMs were systematically computed by directly evaluating the cross-spectral terms between some microphones placed in the array at (i{text{th}}) location ((1 le i le M)) and the remaining microphones placed in the array at (j{text{th}}) location ((j ne i, , 1 le j le M)). As a proof of concept, the SCSM beamforming was used to virtually construct a 32-channel planar Underbrink spiral array by sequentially measuring data using (left( {begin{array}{*{20}c} {32} 2 end{array} } right)) microphone pairs. The resultant 2-D beamforming map of a loudspeaker source was found to be nearly identical to the counterpart result produced when data from 32-channel simultaneous measurements were used. The SCSM technique was then extended to increase the density and aperture of a planar array by constructing a virtual 64-channel planar array from 32-channel simultaneous measurements. For the former case, the source maps were found to be identical to the counterpart results obtained from the existing geometric mean and combined CSM algorithms. However, for the latter case, the SCSM beamforming delivered a noticeably improved focal-resolution along the direction in which there was a virtual increase in aperture. For localizing loudspeaker source(s) in a 3-D domain, the SCSM beamforming implemented using two orthogonal Underbrink arrays was shown to deliver a significantly improved resolution (focal lobe) and unambiguous localization because it considers the complete CSM unlike the multiplicative beamforming and combined CSM algorithms which do not account for the phase-information between the two orthogonal arrays.

The engineering implementation of the multi-channel active noise control (MCANC) system for turboprop aircraft cabin is seriously hampered by its enormous computational complexity. This paper proposes the variable-P-sequential-partial-update filtered-x least mean square (VP-SPUFxLMS) algorithm, which achieves noise reduction performance comparable to that of the multi-channel FxLMS (MCFxLMS) algorithm while significantly reducing the computational complexity. Additionally, considering the time-varying nature of the secondary paths in practical applications, the Eriksson online secondary path modeling (OSPM) method is extended from single-channel to multi-channel, the problems that may be faced when the method is applied to MCANC systems are analyzed, and an improved alternative online secondary path modeling (AOSPM) method is proposed to address the above problems, which exhibits great online modeling capabilities without introducing excessive computational load. Simulation and experiment results validate the noise control performance of the proposed method, and the ANC experiment has achieved an average reduction of more than 15 dB in the sound pressure level (SPL) of the four channels, which fully demonstrates its broad engineering application prospects.

Intensive care unit (ICU) noise is a critical and often overlooked issue, impacting patient recovery and healthcare staff well-being. Existing research primarily relies on costly sound level meters for monitoring noise levels, where the characteristics of noise sources cannot be determined and discriminated. This study employs deep neural networks to detect and classify ICU noise events, enhancing source identification. A cost-effective internet of things-based audio recording and monitoring system has been designed and deployed in three ICUs for data collection. The acoustic event classification system described in the paper integrates convolutional neural networks for event detection, followed by clustering to isolate noise sources. Results demonstrate precise classification, with speech identified as a major contributor in all ICUs. This model offers valuable insights for characterising acoustic sources in typical ICUs, which could be the first step towards tackling the problem of excessive noise in ICUs as well as a starting point for further research in this area.

It is stated in wind farm standards that logarithmic addition and subtraction of L_AF90,T sound pressure levels is “not strictly mathematically correct”. An analytical and experimental study reported in Tonin 2024 (a related article) examines the underlying accuracy of combining statistical noise levels as a general proposition, particularly the L_AF90,T and the L_AF10,T. The objective of that study was to explore the accuracy of combining statistical noise levels and what might influence that accuracy. The objective of this study, as foreshadowed in Tonin 2024, is to apply the results to wind farms. It was concluded in Tonin 2024 that values of D₉₀ (being the difference between the logarithmic sum and actual values of L_AF90,T) are negative in the range 0 to − 3 dB (for the cases in the study), meaning that the logarithmic sum of L_AF90,T for the ambient and source sound pressure level distributions is less than the actual value of L_AF90,T for the combined distribution. As a result, in deriving the wind farm noise level (as a contribution), the actual value of L_AF90,T will be less than that determined by logarithmic subtraction of the individual components. In respect of the question of the underlying accuracy of combining statistical noise levels for wind farms, it is concluded that the difference between the logarithmic addition of the L_AF90,T and the true value is less than 1 dB (for the cases in the study). The results are applied herein to a typical wind farm concluding that the simple energy subtraction method adopted in wind farm guidelines is conservative even allowing for the hypothesis that the fluctuation strength of wind farm noise is not invariant but increases with distance. It is also concluded that if wind farm guidelines were to assess wind farm noise on the basis of L_Aeq,T rather than L_AF90,T then adding a value of 2.5 dB to the derived wind farm noise level L_AF90,T as currently specified in the guidelines (i.e., with D₉₀ = 0 dB) would be conservative even allowing for the hypothesis that the fluctuation strength of wind farm noise is not invariant but increases with distance.

This paper explores the possibility to use statistical energy analysis (SEA)-based computations to synthesize sounds that can be used in a subjective evaluation of the unpleasantness of exterior noises transmitted in the car compartment through the glazing. A medium family car (C-segment car) was placed in a reverberation room. A sound source was placed outside the car. The resulting noise was measured at the driver’s position for nineteen different configurations of glazing. The transmission loss (TL) of each car window was computed using an in-house software and used in a SEA-based vibroacoustic synthesis model. The nineteen corresponding configurations were simulated. A listening test experiment was conducted to compare the signals synthesized from the measurements and from the simulations. The results showed a good agreement between the unpleasantness ratings of each glazing configuration. However, in the case of tempered glasses, a slight difference in the ratings was detected. Further analysis showed that this was due to an inaccurate prediction of the TL of the glazing, around its coincidence frequency. Additional measurements proved that this could be related to an underestimation of the damping. More precisely, because the intrinsic damping of a tempered glass is very low, the additional damping brought by the window seals must be taken into account. Further measurements were made to estimate the TL of a tempered glass mounted on a gasket. The use of these new values in the SEA calculation allowed for the correction of these difference in subjective ratings. The SEA computations can thus be used in the acoustic design process of cars.

Acoustic data from the Perth Canyon, Western Australia, were collected for the 2017 northern migration allowing for detailed acoustic analysis of eastern Indian Ocean pygmy blue (EIOPB) whale songs within a migratory season to explore fine-scale variability in song production. An algorithm was used to follow the unit II signal in time, tracking the change in frequency over the duration of the signal and enabling a comparison of song unit production within and between singing bouts. The results of this analysis indicate that units from within the same song event have relatively consistent characteristics but vary between song events, suggesting it is possible that individual whales may have distinct vocal characteristics. The presence of breaks within a unit was identified as a significant level of variability in song production within the 2017 data set and was seen to increase throughout the season. It is hypothesised that unit breaks may play a role in intra-species communication as well as represent a novel variation to song production that increases song complexity and thus may increase individual fitness through sexual selection.

Metro running causes wheel/rail rolling radiation noise and reflects multiple times between the tunnel wall and the car body. Reverberation in a tunnel increases the interior noise and reduces riding comfort. A statistical energy analysis (SEA) model for a metro train in a tunnel is proposed to predict interior noise and improve ride comfort. The model considers the acoustic excitation caused by wheel/rail rolling, the damping/coupling loss factors, reverberation time in the tunnel/coach, and the equivalent panels. The results show that the error between the simulation and the measured is 3–6 dB; the SEA model is available. The mechanical wave of symmetrical loading may cancel out on the plane of symmetry. At low frequencies, the difference between the internal and external noise is slight (10 dBA), the transmission is robust, and the sound insulation of the car body is weak. In contrast, at high frequencies, the difference is significant (25 dBA). The tunnel reverberation effect increases the sound pressure inside the car by 8–12 dBA than the open-line, and the reverberation will reduce the spatial distribution gradient of the interior noise. Applying noise control treatment on the tunnel’s inner wall can reduce the noise by 5–10 dBA.

The impact of cutting the f-holes in a completed violin was investigated based on two measurable characteristics of the instrument. One of these aspects focused on the signature modes, while the other involved monitoring the graph of the bridge mobility. A particular emphasis was placed on analyzing this graph due to existing literature suggesting the connection of the bridge hill to the presence of f-holes. In the case of two real violins, bridge mobility was measured using an ultra-miniature accelerometer and an impact hammer. Concurrently, signature modes were recorded using Electronic Speckle Pattern Interferometry, an optical technique that performs well on rough surfaces; hence, the violins employed were intentionally left unvarnished. One of the violins lacked f-holes but included the rest of the structural elements. It was measured in stages as the f-holes were cut. The second violin adhered to a standard design but featured slightly wider f-holes, serving as a reference. Additionally, bridge mobility and signature modes were simulated for a finite element violin soundbox both with and without f-holes. Contrary to expectations, both the experiments and simulations revealed the emergence of the Bridge Hill even in the absence of f-holes. However, the alteration of the middle and high-frequency response was evident during the f-hole cutting process, accompanied by the observation of CBR as well as (B_1^-) and (B_1^+) modes.