A wave propagation and vibration based approach for damage identification in structural components

A damage index approach for automatic damage identification and localization based on high frequency wave propagation data and low frequency vibration measurements is presented. Improved ultrasonic and vibration test setups, consisting of either distributed high-fidelity piezoelectric sensor arrays or laser vibrometer, data acquisition boards, signal conditioning and dedicated software have been implemented. In the wave propagation measurements, the data consist of broadband signals due to ultrasonic waves propagating in the structure, while in the vibration measurements they are modal response of the structure produced by the actuators. A damage index comparing the measured dynamical response of two successive states of the structure is introduced as an indicator of the appearance of structural damage. In case of wave propagation measurements, a statistic t, is calculated instantly from the acquired data with a high confidence level. A damaged/undamaged path mechanism is used to approximately locate and characterize the damage using the correlations obtained between the statistic t values at the sensor locations (control points). For vibration based damage identification and localization technique, both piezoelectric patches and the laser vibrometer are used as response sensors in an effort to examine their sensitivity to damage detection. It is found that the laser vibrometer acquisitions produce improved sensitivity and higher accuracy of the damage index when compared to piezo-patches as response sensors. In addition, Modal Assurance Criterion (MAC) has been used to compare and quantify the changes in the modal parameters evaluated from the measurements carried out on the healthy and damaged structure. The main advantage of the damage index approach is that it is relatively insensitive to environmental noise and structural complexities as it is based on the comparison between two adjacent dynamical states of the structure and the baseline for comparison is continuously updated to the previous state. The approach is used to identify various types of defects in the form of loose rivet holes, delaminations due to low velocity impact and added mass for changes in the stiffness, in both metallic and composite structural components with relatively complex geometries. It is shown that the partially automated procedure is able to identify an emerging and/or growing defect, with some degree of confidence.