Research On Damage Identification Of Grid Structures Based On The Vibration Parameters

Just like people may get sick, building structures will inevitably suffer from influence of artificial factors and natural factors and then arises aging and worn during the design, construction and especially during service, and the structural accidents will cause the loss on lives and property. So, structural damage identification has been the hotspot in the current domestic and oversea research. The damage identification methods for complex grid structures have been studied in this paper, based on their dynamic characters. Main contents and achievements are as follow: 1. Systematically research has been carried out on the exist methods of the structural damage identification. And the priorities and drawbacks of the traditional mathematical method and artificial neural network-based method for damage identification have been analyzed. For the measured information is far from complete, the model condensation or the mode shapes extension techniques have to be used in the traditional model updating method. And confidence level of the structural damage identification's result would greatly reduce due to the errors in each procedure. The neural networks have great capability of the pattern recognition, and thus can be well used for structural damage identification with less dependent on the structural model. 2. From the damage identification results of several examples, it is found that, in order to obtain the neural networks with higher pattern recognition performance, it is necessarily for the input and output parameters of the neural networks be normalized. Meanwhile, training with certain level of noise injection will improve the generalization of the neural networks, and will lead to better identification results to the error polluted measured data. 3. Based on analyzing the influence of the damage on the structural modal parameters, grid structural damage signature (GSDS) parameters have been defined, with the first few lower mode frequencies and mode shapes from limited sensor placements, where the normalized mode shapes are used directly instead of the variation of the mode shapes, for the variation of the mode shapes is meaningless. This method can make good use of both advantages of the frequencies and mode shapes. For the variation of the frequencies can well reflect the structural integral performance under damages, and can be easily measured. While the mode shapes are more sensitive to the damages in the structures. At the same time, GSDS can also overcome the shortage with only frequencies or mode shapes used. 4. Based on the study on commonly used sensor placement optimization methods, a sensor placement priority compositor method has been given in this paper. This method takes the model strain energy of the elements and the effective independent of measured mode shapes into consideration. And so it can more sufficiently reflect the structural performance. 5. Based on the study on the formation of grid structures, in which there are plenty of elements and nodes, but the number of nodes is far less than that of the elements. A three-step damage identification method for grid structures is given in this paper. In the first step, the node oriented damage primary localization method is used to...