Research On The Structural Damage Identification Based On Strain Mode Technology

The structural damage detection diagnosis has become more and more important, for some invisible damages do not alert the engineers in time and may result in disastrous consequences and ultimately cause substantial loss of life and property for the yield design date coming.The dynamic characteristics of structures are in closed relationship with the structural parameters, and structural damage will cause the dynamic characteristics shifts correspondently. So the detection and diagnosis of the damage structures can be realized used the dynamic measurements if the mapping relationship between the damage.And the parameters had been founded. The neural network technique has shown great superiority in structural damage detection and diagnosis for its strong non-linear mapping ability, rapid computation and so on.Firstly, several damage identification methods used to identify the structural damage theory are discussed and analyzed. Various theoretical methods, formula and use are introduced mainly from the static, dynamic recognition, and artificial intelligence.Secondly, the basic theory of neural networks is discussed and the basic tenets of damage identification using neural networks are analyzed.Thirdly, the structural damage identification modal and the neural networks are built with the help of ANSYS and MATLAB.Finally, the main contributions and conclusions of the thesis are summarized, and some further research to concerning are brought forward.