2021
DOI: 10.1590/1679-78256400
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Estimation of structural stiffness with the use of Particle Swarm Optimization

Abstract: The paper presents the theoretical background and four applications examples of the new method for the estimation of support stiffness coefficients of complex structures modelled discretely (e.g. with the use of the Finite Element Model (FEM) method based on the modified Particle Swarm Optimization (PSO) algorithm. In real-life cases, exact values of the supports' stiffness coefficients may change for various reasons (e.g. order of fastening, state of the contact surfaces, environment changes, etc.). Because o… Show more

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Cited by 3 publications
(11 citation statements)
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“…In order to minimize the vibration level, an appropriate set of support settings must be determined. The general procedure for finding these settings is: Identification of stiffness values for different settings for each of the adjustable stiffness supports, for example, by performing static tests at the material testing machine; Preparing the modal model of the workpiece itself and assessing its compliance with the actual object using modal parameters identification methods (for example, ERA—Eigenvalue Realization Algorithm or p-LSCFD—poly-reference-Least Square Complex Frequency Domain methods [ 31 , 56 , 58 ]); Selecting cutting process parameters, i.e., depth of cutting, feed speed, spindle speed; Performing a series of simulations of milling process for given sets of support stiffness settings; Assessing the simulation results by comparing a chosen process quality indicator, for example, average tool–workpiece displacement or Root Mean Square (RMS) of the displacements in the time domain; Choosing the set of support settings that assure the best milling conditions. …”
Section: Adjusting the Stiffness Of Supports—general Procedures And S...mentioning
confidence: 99%
See 3 more Smart Citations
“…In order to minimize the vibration level, an appropriate set of support settings must be determined. The general procedure for finding these settings is: Identification of stiffness values for different settings for each of the adjustable stiffness supports, for example, by performing static tests at the material testing machine; Preparing the modal model of the workpiece itself and assessing its compliance with the actual object using modal parameters identification methods (for example, ERA—Eigenvalue Realization Algorithm or p-LSCFD—poly-reference-Least Square Complex Frequency Domain methods [ 31 , 56 , 58 ]); Selecting cutting process parameters, i.e., depth of cutting, feed speed, spindle speed; Performing a series of simulations of milling process for given sets of support stiffness settings; Assessing the simulation results by comparing a chosen process quality indicator, for example, average tool–workpiece displacement or Root Mean Square (RMS) of the displacements in the time domain; Choosing the set of support settings that assure the best milling conditions. …”
Section: Adjusting the Stiffness Of Supports—general Procedures And S...mentioning
confidence: 99%
“…Preparing the modal model of the workpiece itself and assessing its compliance with the actual object using modal parameters identification methods (for example, ERA—Eigenvalue Realization Algorithm or p-LSCFD—poly-reference-Least Square Complex Frequency Domain methods [ 31 , 56 , 58 ]);…”
Section: Adjusting the Stiffness Of Supports—general Procedures And S...mentioning
confidence: 99%
See 2 more Smart Citations
“…Identification of the parameters of the modal model of the boring tool was performed using the ERA ( Eigenvalue Realisation Algorithm ) [ 4 , 32 , 42 ] and the p-LSCFD ( polyreference—Least Squares Complex Frequency Domain ) [ 32 , 43 , 44 ] methods. Measurements were made by uniaxial accelerometers that were mounted to measure vibration for three orthogonal directions at 5 different points ( Figure 5 ).…”
Section: Modal Identification Of Boring Toolmentioning
confidence: 99%