Bio-acoustic wave energy transducer
First Claim
1. A nonlinear acoustic wave producing apparatus comprising:
- a conical housing filled with a resin that holds an array of a plurality of discrete ceramic elements made of a piezoelectric material;
an electronic circuit board that is contained in said conical housing and is wired to each of said plurality of discrete ceramic element;
an electronic control suite containing a programmable digital processor with a non-volatile memory component wherein the programmable digital processor is programmed with an algorithm designed to operate the array of a plurality of discrete ceramic elements, wherein the algorithm initiates the digital processor to perform the steps ofproviding a digital acoustic wave form;
performing a least squares calculation on the acoustic wave form to obtain approximations of kernels h0, h1, h2, h3 from the zero order to the third order;
determining a number of indices k1, k2, k3 for each kernel h0, h1, h2, h3 through Fourier analysis;
transforming kernels h0, h1, h2, h3 into a frequency domain;
assessing which frequency domain kernels h0, h1, h2, h3 have a frequency content with the highest decibel level and discarding the remaining frequency domain kernels;
segmenting the remaining frequency domain kernels h0, h1, h2, h3 into equal overlapping sub-bands;
discarding the overlap between sub-bands;
summing the sub-bands representing segmented frequency domain kernels into whole kernels while taking into account Fourier symmetry property;
placing the whole kernels back into the time domain from the frequency domain using an inverse fast Fourier transform for each kernel; and
solving for y(n) with least squares for the least amount of indices and redundant frequencies, where y(n) is expressed as
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Accused Products
Abstract
A method and apparatus is taught for a signal processing breakthrough that significantly alleviates the “Curse of Dimensionality” (COD) in the characterization of nonlinear physical systems; namely, the reduction in the number of coefficients used to describe the higher order (i.e., nonlinear) kernels in the Volterra series expansion. The latter technique provides the means to evaluate simultaneously from a wide band excitation, all the inter-modulation products up to a specified order by greatly reducing the number of coefficients in the higher order kernel estimation to a manageable set that can be easily manipulated by current personal computers used to enhance a finite element (FE) model that generates a bio-inspired acoustic transducer model.
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Citations
2 Claims
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1. A nonlinear acoustic wave producing apparatus comprising:
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a conical housing filled with a resin that holds an array of a plurality of discrete ceramic elements made of a piezoelectric material; an electronic circuit board that is contained in said conical housing and is wired to each of said plurality of discrete ceramic element; an electronic control suite containing a programmable digital processor with a non-volatile memory component wherein the programmable digital processor is programmed with an algorithm designed to operate the array of a plurality of discrete ceramic elements, wherein the algorithm initiates the digital processor to perform the steps of providing a digital acoustic wave form; performing a least squares calculation on the acoustic wave form to obtain approximations of kernels h0, h1, h2, h3 from the zero order to the third order; determining a number of indices k1, k2, k3 for each kernel h0, h1, h2, h3 through Fourier analysis; transforming kernels h0, h1, h2, h3 into a frequency domain; assessing which frequency domain kernels h0, h1, h2, h3 have a frequency content with the highest decibel level and discarding the remaining frequency domain kernels; segmenting the remaining frequency domain kernels h0, h1, h2, h3 into equal overlapping sub-bands; discarding the overlap between sub-bands; summing the sub-bands representing segmented frequency domain kernels into whole kernels while taking into account Fourier symmetry property; placing the whole kernels back into the time domain from the frequency domain using an inverse fast Fourier transform for each kernel; and solving for y(n) with least squares for the least amount of indices and redundant frequencies, where y(n) is expressed as
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2. A method of generating a mathematical model of a nonlinear acoustic wave form using a programmable digital processor with a non-volatile memory component, comprising the steps of:
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providing a digital acoustic wave form as input to the digital processor; performing a least squares calculation on the acoustic wave form with said digital processor to obtain approximations of kernels h0, h1, h2, h3 from the zero order to the third order; determining a number of indices k1, k2, k3 for each kernel h0, h1, h2, h3 through Fourier analysis with said digital processor; transforming kernels h0, h1, h2, h3 into a frequency domain with said digital processor; assessing which frequency domain kernels h0, h1, h2, h3 have a frequency content with the highest decibel level with said digital processor and discarding the remaining frequency domain kernels with said digital processor; segmenting the remaining frequency domain kernels h0, h1, h2, h3 into equal overlapping sub-bands with said digital processor; discarding the overlap between sub-bands with said digital processor; summing the sub-bands representing segmented frequency domain kernels into whole kernels while taking into account Fourier symmetry property with said digital processor; placing the whole kernels back into the time domain from the frequency domain using an inverse fast Fourier transform for each kernel with said digital processor; and solving for y(n) with least squares for the least amount of indices and redundant frequencies, with said digital processor, where y(n) is expressed as
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Specification