Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/20793
Title: Computationally intelligent estimation of properties for polymer microphone diaphragms by photoacoustic measurement
Authors: Jordovic Pavlovic, Miroslava
Kupusinac, Aleksandar
Djordjević K.
Galovic, Slobodanka
Markushev, Dragan
Nesic, Mioljub
Popović, Marica
Issue Date: 2019
Abstract: This paper presents the application of artificial neural networks for fast and precise characterization of electret microphones with polymer transducer (diaphragm) by photoacoustic measurements. The model consists of two neural networks: the first one for the classification of the microphone type and the second one for the determination of the detector parameters, related to its electronic and geometric features as well as to piezoelectric transducer properties. Obtained prediction has been used for estimation of polymer diaphragms properties by employment of Helmholtz model for sound propagation in small volumes.
URI: https://scidar.kg.ac.rs/handle/123456789/20793
Type: conferenceObject
Appears in Collections:Faculty of Mechanical and Civil Engineering, Kraljevo

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