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DAMAGE IDENTIFICATION METHOD BASED KRIGING MODEL
To improve damage identification efficiency,a damage identification method based on Kriging model was proposed. Sample points were chosen based on Latin hypercube sampling,and Kriging model was built using acceleration frequency response functions corresponding to the damage parameters;then,Kriging model with good precision was used to replace the finite element model to participate in the optimization process. Cuckoo algorithm was used to obtain the damage parameters,where the objective function with the minimum frequency response deviation was constructed. Plane truss model was used to verify the effectiveness of the proposed method. The results show that single damage of location and extent,multiple damages of extent can be both accurately and quantitatively identified by only one measuring point;the maximum error of identification is less than 1%;noise and location of measuring points have a little influence on damage identification results.
DAMAGE IDENTIFICATION METHOD BASED KRIGING MODEL
To improve damage identification efficiency,a damage identification method based on Kriging model was proposed. Sample points were chosen based on Latin hypercube sampling,and Kriging model was built using acceleration frequency response functions corresponding to the damage parameters;then,Kriging model with good precision was used to replace the finite element model to participate in the optimization process. Cuckoo algorithm was used to obtain the damage parameters,where the objective function with the minimum frequency response deviation was constructed. Plane truss model was used to verify the effectiveness of the proposed method. The results show that single damage of location and extent,multiple damages of extent can be both accurately and quantitatively identified by only one measuring point;the maximum error of identification is less than 1%;noise and location of measuring points have a little influence on damage identification results.
DAMAGE IDENTIFICATION METHOD BASED KRIGING MODEL
MA JingJing (Autor:in) / YIN Hong (Autor:in) / PENG ZhenRui (Autor:in) / DONG KangLi (Autor:in)
2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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