Acoustics Australia最新文献

A method to distinguish the surface source and underwater source based on two-dimensional Fourier transform of interference pattern in deep-water environment with an incomplete sound channel is presented in this paper. Considering the modal characteristics of incomplete channel, the normal mode can be divided into three categories: trapped mode, bottom interacting mode and surface interacting-bottom interacting mode. Then, the interference spectrum can be obtained by performing a two-dimensional Fourier transform on the interference pattern. Due to the correlation between the interference structure and the source depth, the types and positions of interference spectral peaks vary at different source depths. Based on this, subspaces can be defined for the interference spectrum, and then the energy ratio of the different modal interference groups in the subspaces can be calculated for source depth discrimination. In this method, the identification of source depth is regarded as a binary classification problem, where the decision threshold is calculated from simulation results under a given false alarm probability. The source depth discrimination can be achieved through comparing the energy ratio with the given decision threshold. The effectiveness of the proposed method is verified using numerical simulations and experimental data.

The increasing application of DIN 4150-3 to above-ground structures such as commercial, residential and particularly heritage buildings in the preliminary planning stage of projects is problematic. DIN 4150-3 is often incorrectly interpreted when applied to Australian scenarios which has the potential for long-term consequences. Applying the DIN 4150-3 guide values for resonant vibration at the correct location (just below the roof) requires the consideration of potential amplification between the foundation and the roof level of the building, which does not appear to be common practice in Australia. A review of the literature found that roof vibration levels are typically 1.5 times higher than that at the foundation, but in practice can be up to four to six times higher, particularly in heritage structure applications. The correct application of DIN 4150-3 results in more stringent guide values at the foundation than those commonly applied in practice in Australia, the practical consequences of which are either an excessive number of pre-construction dilapidation surveys, or the restriction of vibration-intensive items of plant through increased buffer distances, which increases project costs and timelines. This paper proposes an alternative methodology to the application of DIN 4150-3 that, when complemented with the application of BS 7385-2, provides a sensible compromise for Australian scenarios between the competing requirements of asset owners and construction contractors that can be applied to all industrial, commercial and residential receivers, including those with “heritage” status.

University is an important stage of learning for students, so it is vital that higher education spaces are acoustically accessible to all and are places that promote equity and inclusion. The aim of this study was to measure the unoccupied noise levels and reverberation times of all of the classrooms in a typical Australian university to assess acoustic accessibility with a view to planning for a more accessible campus. A total of 166 classrooms were measured and categorised into good, ok, and poor classrooms according to the Macquarie University (MQU) Design Guidelines Review Performance Standards. Regarding unoccupied noise levels, 52% of classrooms were within the recommended < 35 dBA limit. Regarding reverberation times, 65% of classrooms were within the recommended 0.4–0.6 s limit. Finally, 40% of classrooms met both the noise level and reverberation time limit. The plans at the university to incorporate these findings to make the campus more acoustically accessible are discussed, as well as future research avenues so that all students and teachers can flourish.

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.