Application of Improved Particle Swarm Optimization Algorithm to Pipeline Constraint and Load Identification
LI Guangke
TIAN Shuxia
ZHOU Shutang
CHEN Zhenmao
ZHANG Peng
Abstract：A parameter identification method based on improved particle swarm optimization algorithm was proposed for the constraints and load parameter identification of space engine pipelines.Firstly,the finite element model of the pipeline was established,loaded and solved,and the vibration response parameters were obtained.Then,based on the displacement and strain parameters of the structure,the particle swarm algorithm was used to invert the constrained spring stiffness and structural load.The optimization objective was to minimize the residual of the structural response parameters during the forward and inverse processes.MATLAB and ANSYS were used for joint simulation to iteratively solve the constraint and load parameters of the structure.To test the noise resistance of the algorithm,5.00％and 10.00％random noise were applied to the displacement and strain responses obtained from numerical calculations,respectively.Finally,experimental verification was carried out by using testing and analysis data of a simple straight pipeline.The results show that both the standard and improved particle swarm optimization algorithms have reconstruction errors of less than 5％,and the latter has a smaller error compared with the latter.The improved particle swarm algorithm can quickly and accurately dynamically identify structural constraints and load sizes based on structural response parameters,and exhibits good noise resistance.
Keywords：dynamic load detectionimproved particle swarm optimizationjoint simulationparameter identificationvibration response parameters
Publication Date：2024-12-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 19-28 )