Centre Lyonnais d'Acoustique

Phased microphone arrays have become a well-established tool for performing aeroacoustic measurements in wind tunnels (both open-jet and closed-section), flying aircraft, and engine test beds. This paper provides a review of the most well-known and state-of-the-art acoustic imaging methods and recommendations on when to use them. Several exemplary results showing the performance of most methods in aeroacoustic applications are included. This manuscript provides a general introduction to aeroacoustic measurements for non-experienced microphone-array users as well as a broad overview for general aeroacoustic experts.

The problem of localizing and quantifying acoustic sources from a set of acoustic measurements has been addressed, in the last decades, by a huge number of scientists, from different communities (signal processing, mechanics, physics) and in various application fields (underwater, aero, or vibro acoustics). This led to the production of a substantial amount of literature on the subject, together with the development of many methods, specifically adapted and optimized for each configuration and application field, the variety and sophistication of proposed algorithms being sustained by the constant increase in computational and measurement capabilities. The counterpart of this prolific research is that it is quite tricky to get a clear global scheme of the state of the art. The aim of the present work is to make an attempt in this direction, by proposing a unified formalism for different well known imaging techniques, from identification methods (acoustic holography, equivalent sources, Bayesian focusing, Generalized inverse beamforming…) to beamforming deconvolution approaches (DAMAS, CLEAN). The hypothesis, advantages and pitfalls of each approach will be established from a theoretical point of view, with a particular effort in trying to separate differences in the problem definition (a priori information, main assumptions) and in the algorithms used to find the solution. Numerical simulations will be proposed for different source configurations (coherent/incoherent/extended/sparse distributions), and an experimental illustration on a supersonic jet will be finally discussed.

In conventional near-field acoustic holography (NAH) it is not possible to distinguish between sound from the two sides of the array, thus, it is a requirement that all the sources are confined to only one side and radiate into a free field. When this requirement cannot be fulfilled, sound field separation techniques make it possible to distinguish between outgoing and incoming waves from the two sides, and thus NAH can be applied. In this paper, a separation method based on the measurement of the particle velocity in two layers and another method based on the measurement of the pressure and the velocity in a single layer are proposed. The two methods use an equivalent source formulation with separate transfer matrices for the outgoing and incoming waves, so that the sound from the two sides of the array can be modeled independently. A weighting scheme is proposed to account for the distance between the equivalent sources and measurement surfaces and for the difference in magnitude between pressure and velocity. Experimental and numerical studies have been conducted to examine the methods. The double layer velocity method seems to be more robust to noise and flanking sound than the combined pressure-velocity method, although it requires an additional measurement surface. On the whole, the separation methods can be useful when the disturbance of the incoming field is significant. Otherwise the direct reconstruction is more accurate and straightforward.

Rank-based statistics offer an appealing framework to non-parametric robust trend detection. Especially, the Mann–Kendall test detects the presence of a trend in a series. This paper investigates the benefits of using the Mann–Kendall test, which seems to have remained largely unnoticed in the context of vibration-based condition monitoring. Two contributions structure the present paper. First, theoretical foundations of rank-statistics are reminded and the Z-score is introduced, a statistical metric measuring the presence of a trend in a given series. The performance of the Mann–Kendall test is investigated and confronted to different numerical cases involving series of increasing condition indicators. Second, based on this understanding, the Z-score metric is exploited to design two trend-oriented signal processing tools dedicated to vibration-based condition monitoring. Namely, a new tool named the Mannagram is introduced as a dyadic filterbank representation of the trend of indicators series. It shows effective in the informative band selection problem and unveils more interpretable indicators. Besides, a concise representation of trend by frequency bin is introduced and coined the Kendrum. This representation is shown to help the diagnosis by summarising the trend information of series of spectra. Both methods are demonstrated on run-to-failure series of vibration signals from industrial wind turbines.

Array measurements can be contaminated by strong noise, especially when dealing with microphones located near or in a flow. The denoising of these measurements is crucial to allow efficient data analysis or source imaging. In this paper, a denoising approach based on a Probabilistic Factor Analysis is proposed. It relies on a decomposition of the measured cross-spectral matrix (CSM) using the inherent correlation structure of the acoustical field and of the flow-induced noise. This method is compared with three existing approaches, aiming at denoising the CSM, without any reference or background noise measurements and without any information about the sources of interest. All these methods make the assumption that the noise is statistically uncorrelated over the microphones, and only one of them significantly impairs the off-diagonal terms of the CSM. The main features of each method are first reviewed, and the performances of the methods are then evaluated by way of numerical simulations along with measurements in a closed-section wind tunnel.

Total annoyance due to combined noises is still difficult to predict adequately. This scientific gap is an obstacle for noise action planning, especially in urban areas where inhabitants are usually exposed to high noise levels from multiple sources. In this context, this work aims to highlight potential to enhance the prediction of total annoyance. The work is based on a simulated environment experiment where participants performed activities in a living room while exposed to combined road traffic and industrial noises. The first objective of the experiment presented in this paper was to gain further understanding of the effects on annoyance of some acoustical factors, non-acoustical factors and potential interactions between the combined noise sources. The second one was to assess total annoyance models constructed from the data collected during the experiment and tested using data gathered in situ. The results obtained in this work highlighted the superiority of perceptual models. In particular, perceptual models with an interaction term seemed to be the best predictors for the two combined noise sources under study, even with high differences in sound pressure level. Thus, these results reinforced the need to focus on perceptual models and to improve the prediction of partial annoyances.

The MEMS digital loudspeaker consists of a set of acoustic transducers, called speaklets, arranged in a matrix and which operate in a binary manner by emitting short pulses of sound pressure. Using the principle of additivity of pressures in the air, it is possible to reconstruct an audible sound. MEMS technology is particularly well suited to produce the large number of speaklets needed for sound reconstruction quality while maintaining a reasonable size. This paper presents for the first time the modeling, realization and characterizations of a piezoelectric digital loudspeaker based on MEMS technology. Static, dynamic and acoustic measurements are performed and match closely with theoretical results.

Due to the expansion of urban areas, an increasing number of residents are exposed to combined community noise sources. Studies show that the exposure to transportation noise significantly affects health and well-being. Noise annoyance is one of these adverse health effects. Up to now, annoyance due to transportation noise is mostly assessed considering single noise exposure situations neglecting the effects of potential interactions between noise sources. In this study, perceptual phenomena involved in noise annoyance due to combined urban road traffic and tramway noises are assessed in laboratory conditions with imaginary and simulated contexts. The urban road traffic was composed of light vehicles, heavy vehicles, buses, and powered-two-wheelers in different driving conditions. The tramway traffic corresponded to tramways in in-curve operating configurations. It could be shown that the road traffic and tramway traffic partial annoyance responses were influenced by each other. Throughout the experiments the strongest component effect prevailed but secondary phenomena could also be observed. Considering the perceptual phenomena highlighted in the analysis, it is shown that total noise annoyance due to the combined noises can be most adequately predicted by the strongest component model. This result was obtained by calculating partial annoyance responses due to urban road and tramway traffic.

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Interaural time differences (ITDs) and interaural level differences (ILDs) associated with monaural spectral differences (coloration) enable the localization of sound sources. The influence of these spatial cues as well as their relative importance on obligatory stream segregation were assessed in experiment 1. A temporal discrimination task favored by integration was used to measure obligatory stream segregation for sequences of speech-shaped noises. Binaural and monaural differences associated with different spatial positions increased discrimination thresholds, indicating that spatial cues can induce stream segregation. The results also demonstrated that ITDs and coloration were relatively more important cues compared to ILDs. Experiment 2 questioned whether sound segregation takes place at the level of acoustic cue extraction (ITD per se) or at the level of object formation (perceived azimuth). A difference in ITDs between stimuli was introduced either consistently or inconsistently across frequencies, leading to clearly lateralized sounds or blurred lateralization, respectively. Conditions with ITDs and clearly perceived azimuths induced significantly more segregation than the condition with ITDs but reduced lateralization. The results suggested that segregation was mainly based on a difference in lateralization, although the extraction of ITDs might have also helped segregation up to a ceiling magnitude.

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This paper describes the conception, designs consideration and fabrication process of a novel MEMS microphone. The presented microphone not only uses a new architecture, the sensitive part being beams moving within the plane of the substrate, but also uses an innovative detection means with Silicon piezo-resistive nanogauges. Modelization will consider acoustic and mechanical interactions. Besides, at MEMS scale, accurate simulation of the sensor must take into account thermal and viscous boundary layers in acoustics, and we will show that the presented sensor takes benefit from these short scale effects, which leads to achieve theoretical resolution as low as 24dB.

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This paper presents an analytical method for modeling the vibro-acoustic behavior of ribbed non-rectangular orthotropic clamped plates. To do this, the non-rectangular plate is embedded in an extended rectangular simply supported plate on which a spring distribution is added, blocking the extended part of the surface, and allowing the description of any inner surface shapes. The acoustical radiation of the embedded plate is ensured using the radiation impedances of the extended rectangular simply supported plate. This method is applied to an upright piano soundboard: a non-rectangular orthotropic plate ribbed in both directions by several straight stiffeners. A modal decomposition is adopted on the basis of the rectangular extended simply supported plate modes, making it possible to calculate the modes of a piano soundboard in the frequency range [0;3000] Hz, showing the different associated mode families. Likewise, the acoustical radiation is calculated using the radiation impedances of a simply supported baffled plate, demonstrating the influence of the string coupling point positions on the acoustic radiated power. The paper ends with the introduction of indicators taking into account spatial and spectral variations of the excitation depending on the notes, which add to the accuracy of the study from the musical standpoint. A parametrical study, which includes several variations of soundboard design, highlights the complexity of rendering high-pitched notes homogeneous.

This paper is focused on the vibroacoustic behavior of a rectangular ribbed wood panel. This is done by developing an analytical model based on a variational approach, taking into account the kinetic and strain energies of a special orthotropic plate, 11 ribs oriented in a first direction and 1 other strong stiffener oriented in the perpendicular direction, which are considered as beams tied to the plate. A modal decomposition is adopted on the basis of the simply supported orthotropic plate. This allows calculating the modes of the wood panel (ribbed modes) in the frequency range 0-5000 Hz. The acoustical radiation of the baffled panel is also calculated. The radiation coefficients of the ribbed modes are presented and compared, when possible, to similar unribbed plate modes. Finally, the vibroacoustic analysis of the structure shows that an excitation placed on the hard point makes the panel particularly radiative and decreases the apparent critical frequency.