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Optimization Of Model And Measurement Of Parameters Of Microspeaker

Posted on:2017-01-05Degree:MasterType:Thesis
Country:ChinaCandidate:K WangFull Text:PDF
GTID:2518304841464204Subject:Acoustics
Abstract/Summary:PDF Full Text Request
Obtaining from the linear and nonlinear parameters,this article optimize the damping model of microspeaker's suspension to get more correct linear parameter which can fit the measured curves more correct.This article also use the LMS algorithm to calculate the nonliear parameters of microspeaker.This article includes two parts:The first part:Under the viscoelastic effect of the material in microspeaker,the damping of the microspeaker suspension is frequency-dependent.According to the theoretical derivation,the suspension damping in microspeaker can be calculated and the formula of damping can be obtained from the model which calls the SI-LOG model.In the meantime,the experiment shows the data coincidence between the measured curves and the calculated curves which employ the frequency-dependent model of damping in micro-speaker suspension including the impedance,displacement and the frequency response is higher than the frequency-independent model.The second part:Under the large input siganl,the nonlinear parameters Bl(x),Kms(x),Le(x)change with the the displacement.After the polynomial expansion of the nonlinear parameters and the recording the voltage and current under steady state,the nonlinear parameters can be calculated by the LMS algorithm and the program flow which coincide with the measured curves of Klippel.This part shows the LMS algorithm is a practicable method of calculating the nonlinear parameters.According to the two parts work,the more correct linear parameters of microspeaker can be obtained which improve the accuracy between the calculated curves and the measured curves,the nonlinear parameters calculated by LMS algorithm offer a foundation to the nonlinear active control.
Keywords/Search Tags:microspeaker, optimization of damping linear model, nonlinear parameters, LMS algorithm
PDF Full Text Request
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