Real-Time SHM of composite wing in a wind tunnel test using PCA-Based statistics

Abstract

Structural health monitoring could prove particularly valuable in the case of composite aerostructures, where traditional inspection methods for critical components face challenges due to limited accessibility. An effective online SHM system can be achieved by employing fiber optic sensors, facilitating the integration of a 'fiber optic nervous system' into the composite structure, enabling the detection, measurement, and communication of a number of critical structural parameters. While the success of such system relies on selecting the right parameters to be monitored and the right sensing technology, it can also greatly benefit from on-board, real-time processing of the rather large amount of streamed data that ends with some data-driven real-time and continuous assessment as to the current state of the structure: Normal/Abnormal (based, of course, upon previously selected criteria). In this work we demonstrate fiber-optic-based structural health monitoring of a healthy/damaged composite airplane wing in a wind tunnel test. Real-time health assessment is based on Principal Component Analysis (PCA). We utilize two PCA-based measures, the Hotelling's T-squared distribution and the Q-statistics, as fault indicators. These statistics have been demonstrated to exhibit high sensitivity to structural anomalies. A PCA model accompanied by these statistics form a decision support tool that offers dependable real-time information regarding the health of the airborne structure, including the reporting of deviations from a prescribed flight envelope. We demonstrate the performance of the method on real-time structural data gathered in a wind tunnel test, performed on a composite wing. Here, a PCA model was built based on the wing in its healthy state under a nominal loading regime. During the test, the system, processing the data collected from 10 FBGs, using a standard PC, successfully identified deviations, such as overload and initial damage.