Experimental Investigation Of Damage Identification In Beam Structures Based On The Strain Statistical Moment

In the process of construction and service life,the structures' mechanical properties will decrease when the structural damage occur and accumulated,which are mainly caused by the severe environment,human's factors,material aging,impact loading and fatigue loading,furthermore structures will inevitably produce cracks,holes and other different damages.Structures may break down when the structure damage accumulate to some degree.In this thesis,a simply supported steel beam was studied to verify the feasibility and practicality of the damage identification method based on the forth strain statistical moment(FSSM)and the impact of the external load on the proposed method.The details related to these issues are listed as follows:A simply supported steel beam was manufactured and subjected to Gaussian white-noise excitation before and after damage.The strain responses of each measurement point were recorded based on which fourth strain statistical moments were calculated.The proposed two-step technique was implemented to locate the damaged elements of the experimental beam,for which the damage sizes were identified based on the least-square updating algorithm.The experimental results show that the proposed fourth strain statistical moment index and the two-step damage detection technique are effective and feasible for beam-type structures.The impacts of the external load on the damage identification method based on the fourth strain statistical moment were studied,this thesis used the numerical simulation of the simply supported beam model and the experimental model to check impacts of the external load on the proposed method.The results show that the excitation level of the external load has no impact on the proportional relationship between the fourth strain statistical moments of the measured points,and when the position of the external load is changed,the structural damage can also be well located and quantified by using the two-step damage identification method based on the fourth strain statistical moment.