Genetic algorithm application for electrodynamic transducer model identification
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
Wirsansky, E. (2020). Hands-on genetic algorithms with python: Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems. Packt Publishing Ltd., 346.
Barricelli, N. A. (1957). Symbiogenetic evolution processes realized by artificial methods. Methodos, 9 (35-36), 143–182.
Fraser, A. S. (1960). Simulation of genetic systems by automatic digital COMPUTERS Vii. effects of Reproductive RA'L'E, and intensity of selection, on genetic structure. Australian Journal of Biological Sciences, 13 (3), 344. doi: http://doi.org/10.1071/bi9600344
Holland, J. H. (1992). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. The MIT Press. doi: http://doi.org/10.7551/mitpress/1090.001.0001
Small, R. (1971). Direct-radiator loudspeaker system analysis. IEEE Transactions on Audio and Electroacoustics, 19 (4), 269–281. doi: http://doi.org/10.1109/tau.1971.1162200
Moreno, J. N. (1991). Measurement of loudspeaker parameters using a laser velocity transducer and two-channel FFT analysis. Journal of The Audio Engineering Society, 39, 243–249.
DEAP documentation. DEAP 1.3.1 documentation. Available at: https://deap.readthedocs.io/
Novak, A. (2019). Measurement of loudspeaker parameters: A pedagogical approach. Proceedings of the 23rd International Congress on Acoustics. doi: https://doi.org/10.18154/rwth-conv-239247
King, A., Agerkvist, F. (2018). Fractional Derivative Loudspeaker Models for Nonlinear Suspensions and Voice Coils. Journal of the Audio Engineering Society, 66 (7/8), 525–536. doi: http://doi.org/10.17743/jaes.2018.0030
Brunet, P., Shafai, B. (2011). State-Space Modeling and Identification of Loudspeaker with Nonlinear Distortion. Computational Intelligence and Bioinformatics / 755: Modelling, Identification, and Simulation. doi: http://doi.org/10.2316/p.2011.755-054
Copyright (c) 2021 Denys Volkov, Artem Zubkov, Vitalii Didkovskyi
This work is licensed under a Creative Commons Attribution 4.0 International License.
Our journal abides by the Creative Commons CC BY copyright rights and permissions for open access journals.
Authors, who are published in this journal, agree to the following conditions:
1. The authors reserve the right to authorship of the work and pass the first publication right of this work to the journal under the terms of a Creative Commons CC BY, which allows others to freely distribute the published research with the obligatory reference to the authors of the original work and the first publication of the work in this journal.
2. The authors have the right to conclude separate supplement agreements that relate to non-exclusive work distribution in the form in which it has been published by the journal (for example, to upload the work to the online storage of the journal or publish it as part of a monograph), provided that the reference to the first publication of the work in this journal is included.