Designing devices for ultrasonic vibration applications is mostly done by intuitively adjusting the geometry
to obtain the desired mode of vibration at a specific operating frequency. Recent studies have shown
that with optimization methods, new devices with improved performance can be easily found. In this
investigation, a new methodology for designing an ultrasonic amplifier through shape optimization using
genetic algorithms and simplex method with specific fitness functions is presented. Displacements at specific
functional areas, main functionality, and mode frequency are considered to determine the properties
of an individual shape to meet the stated criteria. Length, diameter, position of mountings, and further
specific geometric parameters are set up for the algorithm search for an optimized shape. Beginning
with genetic algorithms, the basic shape fitting the stated requirements is found. After that the simplex
method further improves the found shape to most appropriately minimize the fitness function. At the
end, the fittest individual is selected as the final solution. Finally, resulting shapes are experimentally
tested to show the effectiveness of the methodology.
Designing devices for ultrasonic vibration applications is mostly done by intuitively adjusting the geometryto obtain the desired mode of vibration at a specific operating frequency. Recent studies have shownthat with optimization methods, new devices with improved performance can be easily found. In thisinvestigation, a new methodology for designing an ultrasonic amplifier through shape optimization usinggenetic algorithms and simplex method with specific fitness functions is presented. Displacements at specificfunctional areas, main functionality, and mode frequency are considered to determine the propertiesof an individual shape to meet the stated criteria. Length, diameter, position of mountings, and furtherspecific geometric parameters are set up for the algorithm search for an optimized shape. Beginningwith genetic algorithms, the basic shape fitting the stated requirements is found. After that the simplexmethod further improves the found shape to most appropriately minimize the fitness function. At theend, the fittest individual is selected as the final solution. Finally, resulting shapes are experimentallytested to show the effectiveness of the methodology.
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