A Wavelet Packet Based Method for Structural Damage Assessment

摘要

A statistical pattern classification method based on wavelet packet transform is developed in this study for structural health monitoring. The vibration signals of a structure excited by an impulse load are first decomposed into wavelet packet components. Signal energies of these wavelet packet components are then calculated and sorted according to their magnitudes. Those components that are small in signal energy are discarded since they are easily contaminated by measurement noise. Two damage indicators are then formulated based on the remaining dominant component energy signatures. Thresholds for damage alarming are established using the statistical properties and the one-sided confidence limit of the damage indicators from successive measurements. For demonstration, an experimental study on health monitoring of a steel cantilever I beam is performed. Four damage cases, involving line cracks of different severities in the flanges of one cross section, are introduced. The vibration signals are obtained from an accelerometer installed at the free end of the beam. The results show that the health condition of the beam can be accurately monitored by the proposed method even when the signals are highly contaminated with noise.