The Finite Element Model Correction Of Space Truss Structure Based Neural Net

Since more and more structures are becoming larger and more complex than before, there are many new structures in modern time. At the same time, there are various damage in many existed structures, and they have been used for several decades and are to be surveyed and strengthened. Therefore, structural damage diagnosis has become one of the advancing fronts of civil engineering researches.To forecast structural response, vibration controk state evaluation and health monitor, the first thing is to know the structural dynamic characteristic. Structural dynamic characteristic is related to structural parameter, its theory value can be gained by finite element model (FEM) analysis, its practice value can be achieved by experiment modal analysis. Since the structural dynamic characteristic is changed for its damage, the large difference of structural frequency is existed between the theory value and the practice value. The problem that is to be resolved is how to correct structural FEM to make the theory value equal to the practice value, neural network technique is adapted to the FEM correction for its strong non-linear mapping ability, rapid computation and anti-interference capability. But there are still some problems to be solved such as selection of neural network, determination of structural damage indicator and incompletion of measurement.The project background of this paper is the health monitor of roof truss of Shenzhen citizen center. The object is truss structures that are extensively used in civil engineering, the fixity factor is considered and the damage indicator of frequency and modal are used, and neural network technique that is used for FEM correction is studied in this paper.The space FEM is established when joint link stiff is changed in this paper, the fixity factor is defined to show the element stiff change of joint, theplacement of sensor in an optimal fashion for vibration experiment and modal parameter identification of truss structure are studied.The FEM correction method of truss structure based neural network technique is developed in this paper. Firstly, the space FEM of truss structure that based fixity factor is determined, the relation between fixity factor and structural dynamic characteristic is established according to the change of fixity factor of element stiff matrix. Secondly, according to the change of damage structural frequency and modal, the fixity factor is identified by RBF neural network, then FEM correction of truss is finished.According to the research of this paper, RBF neural net can be well adapted to structure FEM correction, the damage indicator of frequency and modal is used to improve the characteristic that damage indicator of pure frequency is not sensitive to structural damage, the FEM correction of truss structure based neural network can be fully finished.