Autonomous Impact Damage Monitoring in a Stiffened Composite Panel

摘要

This study is concerned with the detection and characterization of impact damage in a stiffened woven composite structure using high frequency Lamb waves and low frequency modal vibrations. The geometric and material complexities of the structure present practical difficulties in the direct analysis of both wave propagation and modal vibration data using theoretical constructs. Improved ultrasonic and vibration test setups consisting of distributed, high fidelity, and surface mounted sensor arrays are used here to determine changes in the dynamical properties of the composite structural components in the presence of damage. The sensors are assumed to provide both the low frequency global response (i.e., modal frequencies and mode shapes) of the structure to external loads and the (local) high frequency signals due to wave propagation effects in either passive or active mode of the ultrasonic array. A damage index, comparing the measured dynamical response of two successive states of the structure is introduced as a determinant of structural damage. The method relies on the fact that the dynamical properties of a structure change with the initiation or growth of damage. A diagnostic imaging tool is used for the interpretation and graphical representation of the indices to enable automated monitoring of the changes in the indices at a given instant of time. The value of the index at a given sensor increases with the proximity of the damage to the sensor. A sensitivity analysis is carried out in an effort to determine a threshold value of the index below which no reliable information about the state of health of the structure can be estimated. It is shown that the automated procedure is able to identify a defect right from its appearance, with some degree of confidence. The feasibility of developing a practical intelligent structural health monitoring system (ISHMS), based on the concept of 'a structure requesting service when needed,' is discussed.