Publication

Optimization of electroacoustic absorbers by means of designed experiments

Hervé Lissek, Romain Boulandet
2010
Journal Articles

Résumé

In multivariate systems, when it comes to identifying actual operating conditions ranges, or optimal settings, the use of constrained optimization is often required. Among the different tools for the engineer to perform such optimization, designed experiments offer accurate performances. In this paper, the optimization process of “electroacoustic absorbers” is investigated by means of response surface methodology. A multivariate linear model is established by a series of designed experiments in order to analyze the modification of electroacoustic absorber performances due to the variation of several constitutive parameters (such as the moving mass of the loudspeaker, the enclosure volume, the filling density of mineral fiber within the enclosure, and the electrical load value to which the loudspeaker is connected), that influence their whole absorbing mechanisms. A simple case study is then provided to illustrate the capabilities of the developed optimization procedure, from which general conclusions on such design methodology, as well as on electroacoustic absorbers sensitivity, are drawn.

Source officielle

https://infoscience.epfl.ch/entities/publication/91873c3e-59bb-4054-bbc9-c1b5ecc31ad0

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Hervé Lissek, Romain Boulandet
2010
Journal Articles

Résumé

Source officielle

https://infoscience.epfl.ch/entities/publication/91873c3e-59bb-4054-bbc9-c1b5ecc31ad0

À propos de ce résultat

Concepts associés (32)

Optimal design

In the design of experiments, optimal designs (or optimum designs) are a class of experimental designs that are optimal with respect to some statistical criterion. The creation of this field of statistics has been credited to Danish statistician Kirstine Smith. In the design of experiments for estimating statistical models, optimal designs allow parameters to be estimated without bias and with minimum variance. A non-optimal design requires a greater number of experimental runs to estimate the parameters with the same precision as an optimal design.

Méthode des surfaces de réponses

thumb|Expériences statistiques : à gauche, un plan factoriel et, à droite, la surface de réponses obtenue par MSR. En statistiques, la méthode des surfaces de réponses (MSR) a pour but d'explorer les relations entre les variables dépendantes et indépendantes impliquées dans une expérience. Elle est due aux travaux de 1951 de George Box et K. B. Wilson. L'idée principale de leur méthode est l'utilisation d'une séquence d'expériences. Box et Wilson suggèrent d'utiliser un modèle à polynôme de second degré, mais concèdent que ce modèle n'est qu'une approximation.

Optimisation multiobjectif

L'optimisation multiobjectif (appelée aussi Programmation multi-objective ou optimisation multi-critère) est une branche de l'optimisation mathématique traitant spécifiquement des problèmes d'optimisation ayant plusieurs fonctions objectifs. Elle se distingue de l'optimisation multidisciplinaire par le fait que les objectifs à optimiser portent ici sur un seul problème. Les problèmes multiobjectifs ont un intérêt grandissant dans l'industrie où les responsables sont contraints de tenter d'optimiser des objectifs contradictoires.

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