This work focuses on an ultrasonic guided wave structural health monitoring (SHM) system development for aircraft wing inspection. The performed work simulate small, low-cost and light-weight piezoelectric discs bonded to various parts of the aircraft wing, in a form of relatively sparse arrays, for cracks and corrosion monitoring. The piezoelectric discs take turns generating and receiving ultrasonic guided waves. The development of an in situ health monitoring system that can inspect large areas and communicate remotely to the inspector is highly computational demanding due to both the huge number of Piezoelectric sensors needed and the high sampling frequency. To address this problem, a general approach for low rate sampling is developed. Compressive Sensing (CS) has emerged as a potentially viable technique for the efficient acquisition that exploits the sparse representation of dispersive ultrasonic guided waves in the frequency warped basis. The framework is applied to lower the sampling frequency and to enhance defect localization performances of Lamb wave inspection systems. The approach is based on the inverse Warped Frequency Transform (WFT) as the sparsifying basis for the Compressive Sensing acquisition and to compensate the dispersive behaviour of Lamb waves. As a result, an automatic detection procedure to locate defect-induced reflections was demonstrated and successfully tested on simulated Lamb waves propagating in an aluminum wing specimen using PZFlex software. The proposed method is suitable for defect detection and can be easily implemented for real application to structural health monitoring.
Alessandro Perelli, Sevan Harput, Luca De Marchi, Steven Freear (2013). Frequency Warping Compressive Sensing for Structural Monitoring of Aircraft Wing. Red Hook, NY : Curran Associates, Inc. [10.1109/ICDSP.2013.6622668].
Frequency Warping Compressive Sensing for Structural Monitoring of Aircraft Wing
PERELLI, ALESSANDRO;DE MARCHI, LUCA;
2013
Abstract
This work focuses on an ultrasonic guided wave structural health monitoring (SHM) system development for aircraft wing inspection. The performed work simulate small, low-cost and light-weight piezoelectric discs bonded to various parts of the aircraft wing, in a form of relatively sparse arrays, for cracks and corrosion monitoring. The piezoelectric discs take turns generating and receiving ultrasonic guided waves. The development of an in situ health monitoring system that can inspect large areas and communicate remotely to the inspector is highly computational demanding due to both the huge number of Piezoelectric sensors needed and the high sampling frequency. To address this problem, a general approach for low rate sampling is developed. Compressive Sensing (CS) has emerged as a potentially viable technique for the efficient acquisition that exploits the sparse representation of dispersive ultrasonic guided waves in the frequency warped basis. The framework is applied to lower the sampling frequency and to enhance defect localization performances of Lamb wave inspection systems. The approach is based on the inverse Warped Frequency Transform (WFT) as the sparsifying basis for the Compressive Sensing acquisition and to compensate the dispersive behaviour of Lamb waves. As a result, an automatic detection procedure to locate defect-induced reflections was demonstrated and successfully tested on simulated Lamb waves propagating in an aluminum wing specimen using PZFlex software. The proposed method is suitable for defect detection and can be easily implemented for real application to structural health monitoring.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.