Genetic algorithm application for electrodynamic transducer model identification


Denys Volkov, Artem Zubkov, Vitalii Didkovskyi

Research object: the adaptation and application of the genetic algorithm for electrodynamic transducer model parameters identification.

Investigated problem: to formulate loudspeaker identification task as an optimization problem, adapt it to the genetic algorithm framework and compare obtained results with classical identification method using added mass.

Main scientific results: the complete genetic algorithm loudspeaker identification procedure is presented, including:

– data acquisition scheme, where the directly measured values for the algorithm application are: voltage at loudspeaker terminals, current through the voice coil and displacement of the moving part

– selection of an appropriate set of genes of an individual

– derivation of the fitness function for assessing the quality of the identified parameters, which can also be used to identify other types of electroacoustic transducers

Also, the advantages of this method in comparison with the classical method of identification using added mass are considered, that are its versatility and ability to quickly configure and adapt for research and experimentation with different loudspeaker models and different types of transducers used in acoustics.

Area of practical use of the research results: the proposed genetic loudspeaker model identification scheme can be directly applied on practice to speed up research and development tasks in electroacoustics and other related fields that require frequent experimentation with different types of transducer models.

Innovative technological product: genetic algorithm based loudspeaker identification scheme that can be applied to identify various model of electrodynamic transducers.

Scope of application of the innovative technological product: electroacoustics, loudspeaker design, audio systems

FULL PAPER

How to cite paper:

Volkov, D, , Zubkov, A, , Didkovskyi, V, (2021). Genetic algorithm application for electrodynamic transducer model identification. ScienceRise, 4, 48-57. doi:https://doi.org/10.21303/2313-8416.2021.002008