Two-StageDamageDetectionMethodBasedon ImprovedParticleSwarm OptimizationAlgorithm

In orderto solvestructural multi-damageidentification problem,atwo-stage identificationmethodbasedontheparticleswarm optimization (PSO)algorithm andthe Bayesiantheorywasproposed.Inthismethod,structuralmodalstrainenergy (MSE)and frequencyareconsideredastwoinformationsources,andthe methodsbasedonfrequency changeand MSE dissipationratioareutilizedtoextractdamageinformation.Then,the Bayesiantheoryisutilizedtointegratethetwoinformationsourcesandpreliminarilydetect structuraldamagelocations.Finally,the PSO algorithm isadoptedto preciselyidentify structuraldamagelocationsandextents.Inordertoimprovetheidentificationresultsofa simplePSOalgorithm,threeimprovedstrategies,particleposition mutation,elitistmicro- searchanddoubleconvergencecriterion,werepresented.Thesimulationresultsforatwo- dimensionaltrussstructureshowthattheBayesiantheorycanidentifythesuspecteddamage locations,theimproved PSO algorithm can preciselydetectthedamageextent,andthe identificationprecisionofthePSOalgorithm withthethreeimprovedstrategiesisobviously betterthanthoseoftheotherPSOalgorithmsandthegeneticalgorithm.