Αντικείμενο της παρούσας διπλωματικής εργασίας είναι η μελέτη της ακουστικής παρακολούθησης και ανάλυσης λειτουργίας μηχανών σε βιομηχανικές και μη εφαρμογές. Ασχολούμαστε κυρίως με την παρακολούθηση του θορύβου που εκπέμπουν οι μηχανές και μας ενδιαφέρει ο εντοπισμός των ηχητικών πηγών (πηγών θορύβου) προκειμένου να ληφθούν οι κατάλληλες ενέργειες. Για το σκοπό αυτό παρουσιάζονται μέθοδοι, «οπτικοποίησης» του ηχητικού πεδίου, οι οποίες κάνουν πιο εύκολη τη διαδικασία εντοπισμού. Σε αυτή τη διπλωματική εργασία παρουσιάζοντα οι βασικές αρχές της ακουστικής θεωρίας, οι βασικές διατάξεις που χρησιμοποιούνται για τη μέτρηση του ήχου. Στη συνέχεια περιγράφονται οι υπάρχουσες μέθοδοι χαρτογράφησης του ηχητικού πεδίου για τον προσδιορισμό των ηχητικών πηγών, οι διατάξεις που χρησιμοποιούνται για το σκοπό αυτό και τέλος παραθέτονται κάποιες εφαρμογές. / The object of this diploma paper is the acoustic attendance and analysis of machines in industrial and other applications. Our main concern is the noise emission from the machines and we are also interested on locating the sound (noise) sources in order to take proper actions. For this purpose methods of sound “visualization” are introduced, that make easier the process of locating the sources. In this diploma paper we also introduce the basic principles of acoustic theory and the used arrays for sound measurement. Next is the description of the existing methods of mapping the sound field in order to detect the sound sources, the instruments used for this purpose and in the end some applications.

This thesis is aimed at identifying the noise sources of a wheeled tractor to reduce the noise levels below the legislative limits by controlling noise sources through proper methodologies. The study focuses firstly on identifying the noise sources of a wheeled tractor by using proper noise source identification techniques. These techniques can be summarized as sound intensity measurements, sound power level determination studies and spectral analysis of the noise data acquired in the tests. Simple sound intensity mapping techniques are used and the intensity contour maps are generated to identify the noise sources. Most important and effective noise sources are identified and the critical noise sources are focused to apply appropriate noise control strategies not only at the prototype production stages but also at the early design stages. Consequently, upon consideration of both structure-borne and flow-induced noise, the pass-by noise level and the operator&rsquo / s ear noise levels of the tractor are reduced by nearly 3 dB (A) through application of proper noise control strategies.

The diploma thesis deals with the application of acoustic methods for evaluating the technical condition of the shock absorbers. Analysis of acoustic radiation during damping operation leads to the definition of a new non-contact diagnostic methodology that can determine the condition of the shock absorbers. The first part of the thesis focuses on the noise radiation of the shock absorbers, which is caused by discontinuous dumping. Further, the methods for the noise source localization available at The Institute of Machine and Industrial Design are described – with their functionalities, advantages and limitations. Based on all the information, an appropriate method is selected and used in the experimental part of this work. Then, aeration and removing the full volume of oil with damage of the shock absorber tube are caused (induced) on several types of the shocks. Noise radiation is measured by a microphone array and by a sound meter; the acoustic maps, frequency spectra and the synchronous filtration graphs are calculated from the measured data. From the differences in the acoustic radiations of each shock condition, a suitable diagnostic criterion for a specific shock absorber is defined. The final part discusses obtained results. Based on these results, a general diagnostic methodology, applicable to any type of shock absorber, is formulated.

<p dir="ltr">The CFD-CAA method combines computational fluid dynamics (CFD) and computational aeroacoustics (CAA) techniques to analyze the interaction between fluid flow and the generation and propagation of sound. CFD is primarily concerned with simulating fluid flow patterns, while CAA focuses on predicting noise generation and its propagation in fluids. The CFD-CAA method provides a powerful tool for understanding and predicting the acoustic behavior of turbulent flows. By combining the strengths of CFD and CAA, this approach provides more precise and comprehensive analyses across various fields, thereby contributing to enhanced designs and noise control strategies.</p><p dir="ltr">Within industrial applications, a primary concern is noise source identification. This process enables engineers to locate and quantify the strength of noise sources within a system, facilitating the implementation of more effective strategies during the design process. A novel methodology, computational statistically optimized near-field acoustic holography (C-SONAH), is proposed to virtually identify aeroacoustic sources. Initially, sound pressure is obtained using the CFD-CAA method, followed by the application of the SONAH algorithm to locate acoustic sources and predict the sound field. C-SONAH offers computational advantages over direct CAA methods for simulating sound produced by systems with rotating elements, as CAA analyzes sources on the moving elements, making sound field calculation computationally expensive. The SONAH procedure converts these rotating sources into a series of equivalent stationary planar or cylindrical waves, reducing the number of sources and the time required to compute the sound field from each source. This methodology was demonstrated by characterizing the aerodynamic noise produced by a bladeless fan. The sound pressure level obtained by C-SONAH method was validated by the data predicted by the direct CFD-CAA method. Acoustic maps were reconstructed at different locations and frequencies, revealing that the C-SONAH method can predict noise sources generated by airflow and rotating components within the fan. Thus, it serves as an effective tool for understanding the aeroacoustic noise generation mechanism and guiding the design optimization of similar products.</p><p dir="ltr">The CFD-CAA method is also a powerful tool for design optimization. Computational simulations are typically less expensive and time-consuming than building and maintaining experimental setups, particularly for large or complex projects. Additionally, simulations reduce the need for multiple physical prototypes, which can shorten the development cycle. CFD-CAA simulations provide detailed flow and acoustic field data, including variables that may be difficult or impossible to measure experimentally, such as pressure distributions, velocity fields, and turbulent structures. In this dissertation, aeroacoustic characteristics and flow field information of vortex whistles were investigated using the CFD-CAA method. The simulation results clearly illustrate the swirling motion created in the vortex whistle cylinder and also demonstrate the linear frequency versus flow rate relationship characteristic of the whistle. The design of the vortex whistle was optimized based on the acoustic response and flow resistance by both simulations and experiments. The results suggest that the whistle with a thin inlet exhibits the best performance at high flow rates, while the whistle with a scale of 0.5 is the most sensitive to low flow rates, making it suitable for pediatric applications.</p><p dir="ltr">In CFD-CAA simulations, the time step typically cannot be too small due to limited computational resources. This constraint results in an aliasing error in spectral analysis. Consequently, an anti-aliasing operation prior to sampling is necessary to eliminate such errors from the acoustic source terms. In the present study, an anti-aliasing filter based on the compact finite difference formulation was designed within a time-domain, compact filter scheme. This filter was directly applied to the Navier-Stokes solver prior to sampling for CAA analysis. A cavity flow case was simulated to validate this mitigation strategy. The results indicate that the artificial spectral peak induced by aliasing error is removed without affecting other signature peaks. The anti-aliasing filter was also applied to more complex cases for predicting the acoustic field of a vortex whistle. The acoustic field around the vortex whistle, with both constant and variable inlet flow rates, was simulated, and the aliasing peak was successfully removed. Although the peak magnitudes decreased slightly due to the filter, the signature frequencies remained unchanged. Thus, the simulation with anti-aliasing operation can predict acoustic features without introducing aliasing errors, even if the time step is not sufficiently small, thereby significantly reducing simulation time.</p><p dir="ltr">In engineering applications, once noise sources are identified, the subsequent concern is noise reduction. An effective strategy for noise reduction involves acoustical absorbing materials to minimize noise emissions from components. Traditionally, experiments in engineering applications have focused on surface treatments to explore noise control techniques. However, the CFD-CAA method commonly assumes smooth and purely reflective wall surfaces. Consequently, there is growing interest in incorporating impedance boundary conditions into the CFD-CAA method. Since impedance boundary conditions are defined in the frequency domain, while CFD-CAA simulations operate in the time domain, direct implementation is not feasible. To address this issue, several methods have been proposed to define time-domain impedance boundary conditions in simulations. In the present study, a wall softness model was implemented in the CFD-CAA method and to examine a vortex whistle featuring an acoustically permeable surface. In simulations, an impedance boundary condition representing the properties of melamine foam was defined over the surface of a cylindrical cavity. The simulation results were validated against experimental data obtained from a vortex whistle with melamine foam. The findings revealed that the impedance of the melamine foam contributed to noise reduction at high frequencies. Additionally, at low airflow rates, the impedance boundary condition enhanced the signal-to-noise ratio for the low-frequency peak, which is advantageous in clinical applications.</p>

La caractérisation expérimentale de sources acoustiques est l'une des étapes essentielles pour la réduction des nuisances sonores produites par les machines industrielles. L'objectif de la thèse est de mettre au point une procédure complète visant à localiser et à quantifier des sources acoustiques stationnaires ou non sur un maillage surfacique par la rétro-propagation d'un champ de pression mesuré par un réseau de microphones. Ce problème inverse est délicat à résoudre puisqu'il est généralement mal-conditionné et sujet à de nombreuses sources d'erreurs. Dans ce contexte, il est capital de s'appuyer sur une description réaliste du modèle de propagation acoustique direct. Dans le domaine fréquentiel, la méthode des sources équivalentes a été adaptée au problème de l'imagerie acoustique dans le but d'estimer les fonctions de transfert entre les sources et l'antenne, en prenant en compte le phénomène de diffraction des ondes autour de l'objet d'intérêt. Dans le domaine temporel, la propagation est modélisée comme un produit de convolution entre la source et une réponse impulsionnelle décrite dans le domaine temps-nombre d'onde. Le caractère sous-déterminé du problème acoustique inverse implique d'utiliser toutes les connaissances a priori disponibles sur le champ sources. Il a donc semblé pertinent d'employer une approche bayésienne pour résoudre ce problème. Des informations a priori disponibles sur les sources acoustiques ont été mises en équation et il a été montré que la prise en compte de leur parcimonie spatiale ou de leur rayonnement omnidirectionnel pouvait améliorer significativement les résultats. Dans les hypothèses formulées, la solution du problème inverse s'écrit sous la forme régularisée de Tikhonov. Le paramètre de régularisation a été estimé par une approche bayésienne empirique. Sa supériorité par rapport aux méthodes communément utilisées dans la littérature a été démontrée au travers d'études numériques et expérimentales. En présence de fortes variabilités du rapport signal à bruit au cours du temps, il a été montré qu'il est nécessaire de mettre à jour sa valeur afin d'obtenir une solution satisfaisante. Finalement, l'introduction d'une variable manquante au problème reflétant la méconnaissance partielle du modèle de propagation a permis, sous certaines conditions, d'améliorer l'estimation de l'amplitude complexe des sources en présence d'erreurs de modèle. Les développements proposés ont permis de caractériser, in situ, la puissance acoustique rayonnée par composant d'un groupe motopropulseur automobile par la méthode de la focalisation bayésienne dans le cadre du projet Ecobex. Le champ acoustique cyclo-stationnaire généré par un ventilateur automobile a finalement été analysé par la méthode d'holographie acoustique de champ proche temps réel. / Experimental characterization of acoustic sources is one of the essential steps for reducing noise produced by industrial machinery. The aim of the thesis is to develop a complete procedure to localize and quantify both stationary and non-stationary sound sources radiating on a surface mesh by the back-propagation of a pressure field measured by a microphone array. The inverse problem is difficult to solve because it is generally ill-conditioned and subject to many sources of error. In this context, it is crucial to rely on a realistic description of the direct sound propagation model. In the frequency domain, the equivalent source method has been adapted to the acoustic imaging problem in order to estimate the transfer functions between the source and the antenna, taking into account the wave scattering. In the time domain, the propagation is modeled as a convolution product between the source and an impulse response described in the time-wavenumber domain. It seemed appropriate to use a Bayesian approach to use all the available knowledge about sources to solve this problem. A priori information available about the acoustic sources have been equated and it has been shown that taking into account their spatial sparsity or their omnidirectional radiation could significantly improve the results. In the assumptions made, the inverse problem solution is written in the regularized Tikhonov form. The regularization parameter has been estimated by an empirical Bayesian approach. Its superiority over methods commonly used in the literature has been demonstrated through numerical and experimental studies. In the presence of high variability of the signal to noise ratio over time, it has been shown that it is necessary to update its value to obtain a satisfactory solution. Finally, the introduction of a missing variable to the problem reflecting the partial ignorance of the propagation model could improve, under certain conditions, the estimation of the complex amplitude of the sources in the presence of model errors. The proposed developments have been applied to the estimation of the sound power emitted by an automotive power train using the Bayesian focusing method in the framework of the Ecobex project. The cyclo-stationary acoustic field generated by a fan motor was finally analyzed by the real-time near-field acoustic holography method.