Acoustics Australia最新文献

The cascade’s response function can be used to effectively deal with the unsteady response of the interaction between the harmonic turbulence and the cascades. Based on this function, this paper presents the formulas for the stator broadband and tonal noises, whose inflow models are different from each other. The broadband noise comes from the impact of the random turbulence wave in the rotor wake on the stator, while the tonal noise comes from the interaction between the periodic rotor wake and the stator. According to the formulas for predicating the two kinds of noise, their inflow models are different from each other. Comparing with the test models of subsonic fan, the prediction models of the broadband and tonal noise prove to be correct. Meanwhile, the influence of the blade number on stator tonal and broadband noise is carried out through the prediction models, and the results are summarized that (1) the greater the number of blades, the higher the broadband sound power level of the stator in the high frequency. (2) An increase in the number of blades can “cut off” the tonal noise of the stator at BPF. So, reasonable arrangement of the number of stator and rotor blades is significant to the passive suppression of stator noise.

Long-term data of underwater passive acoustic monitoring (PAM) collected from two sites of pygmy blue whale presence within Australia, the continental shelf off Portland (38.5° S, 141.2° E) and the Perth Canyon (32° S, 115° E) were analysed to compare the acoustic behaviour of eastern Indian Ocean pygmy blue (EIOPB) whales. Pygmy blue whale song detection was consistently higher at the Perth Canyon site than at the Portland sample site. Statistical analysis found there to be a significant difference in the production of song and phrase variants between sites (p < 0.01) with a shorter two-unit (P2) song variant being more common in the Perth Canyon area, while the traditional three-unit (P3) song variant was more frequent off Portland. This was supported by manual and feature space analysis techniques. Increasing song complexity was observed in the form of phrases with broken song units, a phenomenon that was first observed at the Portland site on isolated occasions but has occurred and proliferated in the Perth Canyon area from 2016 onwards. Analysis of environmental conditions indicated that increased background noise due to multiple EIOPB whales vocalising, as well as water depth, may influence song length. This was reflected by songs made up of shorter phrases dominating in higher background noise conditions and deeper water, while longer more complex phrase types dominate in quieter, shallower conditions. Further research is recommended to isolate any potential influence of environmental factors on song production.

Machine health condition monitoring is evidently a crucial challenge nowadays. Unscheduled breakdowns increase operating costs due to repairs and production losses. Scheduled maintenance implies taking the risk of replacing fully operational components. Human expertise is a solution for an outstanding expertise but at a high cost and for a limited quantity of data only, the analysis being time-consuming. Industry 4.0 and digital factory offer many alternatives to human monitoring. Time, cost and skills are the real stakes. The key point is how to automate each part of the process knowing that each one is valuable. Leaving aside scheduled maintenance, this paper copes with condition-based preventive maintenance and focuses on one fundamental step: the signal processing. After a brief overview of this specific area in which numerous technologies already exist, this paper argues for an automated signal processing at an expert level. The objective is to monitor a system over days, weeks, or years with as great accuracy as a human expert, and even better in regard to data investigation and analysis efficiency. After a data validation step most often ignored, any multimodal signal (vibration, current, acoustic, …) is processed over its entire frequency band in view of identifying all harmonic families and their sidebands. Sophisticated processing such as filtering and demodulation creates relevant features describing the fine complex structures of each spectrum. A time–frequency feature tracking constructs trends over time to not only detect a failure but also to characterize and localize it. Such an automated expert-level processing is a way to raise alarms with a reduced false alarm probability.

In this paper, the two-zone sound field reproduction problem is investigated with a newly proposed method. The aim of the two-zone reproduction problem is to achieve sound field reproduction in the bright zone while keeping the sound field energy in the dark zone as low as possible. The main difference between the proposed method and the conventional method is that the sound field control in the dark zone is not limited to a small number of measurement points on the region boundary but to measurement points throughout the whole dark zone. For practical reasons, the whole region is discretized into a grid, and the grid selection method is also provided in this paper. Simulations are performed to compare the performances of the proposed and conventional methods with different virtual source directions, and a comparison of the robustness to the regularization parameter shows that the proposed method is less sensitive to the selection of the regularization parameter. Finally, an experiment is performed with a circular loudspeaker array in a real listening room. A quieter dark zone is achieved by the proposed method while keeping the reproduction error in the bright zone close to that of the conventional method, similar to the simulation results. These outcomes verify that the proposed method performs well in both free-field and reverberation environments.

In this paper, the authors discuss about the future challenges of condition monitoring in an industrial context. One of the authors is Line Manager at Data Processing & Analytics for Equipment, Industry 4.0 & MES Products division of Tetra Pak Packaging Solutions S.p.A., a multinational company that approached condition monitoring and diagnostics fifteen years ago. So far, they have gained experience and have a clear idea of what the Industrial field expects in the coming years. In this paper, the analysis of a specific case study is an opportunity to suggest more general research themes on condition monitoring.

The wind industry has seen tremendous growth during the past two decades, with the global cumulative installation capacity reaching more than 650 gigawatts by the end of 2019. Despite performance and reliability improvements of utility-scale wind turbines over the years, the industry still experiences premature component failures, leading to increased operation and maintenance (O&M) costs. Among various turbine components, gearboxes—and, more broadly, drivetrains—have shown to be costly to maintain throughout the design life of a wind turbine. The problem of premature component failure is industry wide. As early as 2007, the US Department of Energy (DOE) started to address this challenge through the National Renewable Energy Laboratory’s (NREL’s) reliability initiative that first focused on gearboxes and more recently expanded to entire drivetrains. The wind turbine drivetrain condition monitoring and wind plant O&M research that is the subject of this paper is part of the NREL initiative and includes a few research and development (R&D) activities conducted during the 2010s. These activities included technology evaluation during the first few years; novel monitoring technique investigation (specifically, compact filter analysis) during the middle years; and data and physics domain modeling for fault detection and prediction in recent years. A high-level summary of these activities is provided in this paper along with some key observations from each activity. Most of the work discussed has been published and can be referred to for more information. They reflect the expected evolution of wind turbine condition monitoring and O&M in the US market—primarily, a land-based perspective. In addition, we have identified several R&D opportunities that can be picked up by the research community to help industry advance in related areas, making wind power more cost competitive in the future.

Experimental studies were conducted at a hemi-anechoic chamber to investigate the effectiveness of trailing-edge (TE) serration designs for reducing aerodynamic noise of a propeller. The propeller noise was measured under different speeds in both the vertical and horizontal directions. The thrust force produced by the propeller was also measured at rotational speeds. The flaplet, concave and sawtooth shapes of serration were integrated on the TE of baseline propeller to obtain three different serrated propellers. The results show that the flaplet, concave and sawtooth propellers improve the thrust force more than 10% on the basis of baseline propeller. Three types of TE serration all managed to attenuate large amount of noise, while the sawtooth serrations are more effective than flaplet and concave serrations in a wider frequency range. Then, the serration distribution length (DL) of sawtooth propeller was trimmed to other three different values to obtain the 3/4-DL, 1/2-DL and 1/4-DL propellers. The 3/4-DL propeller exhibited best comprehensive performance, by an average of 2.7 and 3.0 dB noise reduction in tested two positions and simultaneously generated overall 6.7% higher thrust force than did the baseline propeller. The morphological and parametric effects of TE serration in current studies are more significant in a relative high Reynolds number (1.4 × 10⁶).

Vibration signals collected from machines can contain rich machine degradation information, such as impulsiveness and cyclo-stationarity. In the field of machine condition monitoring (MCM), quantification of impulsiveness has attracted many researchers’ interests because impulsiveness often indicates an occurrence of incipient faults. Impulsiveness-based health indicators (HIs) (e.g., Gini index, kurtosis, entropy, smoothness index, etc.) are some kinds of statistical parameters that can quantify the impulsiveness of vibration signals. Hence, they have been widely studied during recent years for MCM. However, a thorough comparitive study of those HIs is seldom reported. This paper aims to compare seven impulsiveness-based HIs including kurtosis, skewness, smoothness index, negative entropy, Gini index, Hoyer measure, and the ratio of L2 to L1 norm for MCM according to three properties including the robustness to the length of a signal, the gradient for sparsity or impulsiveness, and quantification of impulsiveness and cyclo-stationarity. Among the seven HIs, it was experimentally found that the Gini index is better than the other indicators to satisfy the three suggested properties for MCM.

This study aims to examine the influence of colour exposure on noise annoyance. Previous studies in the literature have focused mostly on the effects of colour exposure on loudness judgements; however, due to the cognitive nature of multisensory perception, the influence of colour on noise annoyance also needs to be investigated. Our experiments were designed to administer non-information-carrying sound signals (i.e. white noise) and visual stimuli (i.e. abstract colour samples) and to limit visual and auditory contextual information. Participants were asked to evaluate noise annoyance on an 11-point International Commission on Biological Effects of Noise (ICBEN) scale. The experiments were conducted in the form of audio-visual tests. During these tests, random combinations of three white noise sound samples with sound pressure levels of 66 dB(A) (−4 dB[A] acoustic condition), 70 dB(A) (0 dB[A] acoustic condition) and 74 dB(A) (+4 dB[A] acoustic condition), and six visual stimuli, including the elementary colours of the Natural Colour System (NCS)—yellow (Y), red (R), blue (B), green (G), white (W) and black (S)—were presented to a total of 42 participants. The black colour sample was used to measure the audio-only control condition for the three white noise sound samples. The results of the study reveal that the effects of sound, the effects of colour and the interaction effects of colour and sound on perceived noise annoyance were statistically significant. The effects of colour on the loudness evaluations of the previous studies and the effects of colour on noise annoyance evaluations presented in this study show very similar and concordant results, indicating that the effects of colour on noise annoyance depend on the sound pressure level (SPL). The results indicate that the hue contrasts of red–green, red–blue and yellow–blue and the lightness contrast of yellow–blue influenced perceived noise annoyance when the SPL was low or high. Within the contrast pairs, red and yellow were perceived to be annoying, whereas blue and green were perceived to be non-annoying.