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October 13, 2021
Journal Article
Title

Automatic Classification of Enclosure-Types for Electrodynamic Loudspeakers

Abstract
This article deals with the realization of an automated classification of loudspeaker enclosures. The acoustic load of the enclosure is reflected in the electrical impedance of the loudspeaker and is hence detectable from the point of view of the power amplifier. In order to classify the enclosures of passive one-way speakers, an artificial neural network is trained with synthetic impedance spectra based on equivalent electrical circuit models. The generalization capability is validated with measured test sets of closed, vented, band-pass and transmission-line enclosures. The resulting classification procedure works well within a synthetic test set. However, a good generalization to the measured test data requires further investigations to achieve better separation between the different vented enclosure types.
Author(s)
Werner, Johannes
Hochschule Mittweida  
Fritsch, Tobias  
Fraunhofer-Institut für Digitale Medientechnologie IDMT  
Journal
AES E-Library. Online resource  
Conference
Audio Engineering Society (AES Fall Convention) 2021  
Language
English
Fraunhofer-Institut für Digitale Medientechnologie IDMT  
Keyword(s)
  • Transducers

  • Sound Field Control

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