# Micah Shepherd, Xi Chen, Timothy W. Leishman, Scott D.Sommerfeldt Acoustics Research Group

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Experimental Equalization of a One-Dimensional Sound Field Using Energy Density and a Parametric Equalizer. Micah Shepherd, Xi Chen, Timothy W. Leishman, Scott D.Sommerfeldt Acoustics Research Group Department of Physics and Astronomy Brigham Young University - PowerPoint PPT PresentationTRANSCRIPT

Experimental Equalization of a One-Dimensional Sound Field Using Energy Density and a Parametric EqualizerMicah Shepherd, Xi Chen, Timothy W. Leishman, Scott D.Sommerfeldt

Acoustics Research GroupDepartment of Physics and AstronomyBrigham Young University

148th Meeting of the Acoustical Society of America18 November 2004

Background and Traditional TechniqueBackgroundSound fields in rooms do not have ideal responsesSound field equalization compensates for room effects using filtersTraditional techniquesExcite room using pink noiseMeasure pressure response at one locationCut and boost in nth octave bands using graphic equalizer to produce desired responseBetter control using parametric equalizersVariable frequencyVariable QProblemsSpatial variance of sound fieldMicrophone at nodesLimited frequency and gain adjustmentNeed for a better approach

Search for an Improved TechniqueMeasure transfer function between source and receiver in 1-D sound fieldThree casesSingle point mean-squared pressureSpatially averaged mean-squared pressure (potential energy density)Single point total energy densityUse normalized inverses of the responses as equalization filters

Experimental Setup

Energy DensityPressure gradient method Estimate particle velocity using pressure gradient

Energy Density is then

2 microphone transfer function method Developed by Chung and Blaser

Solve for incident and reflected pressure and reflection coefficients at microphone positions

Derive particle velocity and energy density from result

Difference in ED Estimations

Unequalized FieldMean-Squared Pressure FieldEnergy Density Field

Ideal Inverse Filters From Measured Field

Ideal Equalized Pressure FieldsMean-Squared Pressure EQEnergy Density EQ

Comparison of Ideal Energy DensityFilter and Parametric EQ Filter

Equalized Pressure FieldsParametric ED EQIdeal ED EQ

Spatially Averaged Pressure Responses: Ideal and Parametric

ConclusionsEnergy density equalization approximates spatially averaged pressure equalization in a 1-D sound fieldA discrete ED measurement can be used to equalize a 1-D sound field better than a discrete pressure measurementParametric equalizers can be used to approximate ideal ED filters, but with notable errors

Future workConduct more general tests in a 1-D field with variable side-branch source positionsTest energy density equalization methods in 3-D sound fieldsTest energy density equalization methods using multiple sourcesDevelop adaptive filtering techniques

Thank you

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