Abstract
First establish a dynamic model of tower crane in the load lifting process, the lifting load is solved under two work conditions.Then establish the FEM(finite element analysis) model of the tower crane under the normal and the damage condition. Get the dynamic displacement of the normal and the damage status under the lifting dynamic load. With wavelet packet decomposition and SVM(Support vector machines) multi-classification algorithm, a multi-fault classifier is constructed, and applied to the fault diagnosis of tower body. The results of the study show that the multi-fault classifier has such advantages as simple algorithm and excellent capability of fault classification, and it can not only diagnose the structural damage status, but also determine the positions of structural damage. This will be a new search on tower crane structural health diagnosis.
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