Web App Conference & Proceedings: 8th European Workshop On Structural Health Monitoring (EWSHM 2016)

8th European Workshop On Structural Health Monitoring (EWSHM 2016)

5-8 July 2016, Spain, Bilbao
Right Now in Bilbao 10:35 Wed 11

17:50 Tuesday 5. Jul - A3A

Model-assisted performance qualification of a distributed SHM system for fatigue crack detection on a helicopter tail boom

Abstract »In the recent years, the problem of real-time structural monitoring for the on-board health assessment of operating aircrafts has become a critical research topic and extensive studies are available in literature. Many different sensing technologies can be exploited in a Structural Health Monitoring (SHM) scenario, either based on local or distributed sensor networks, the second being particularly suited to monitor large structures, such as airframes. However, the reliability of any system must be demonstrated and quantified using acceptable established procedures used by the industry and very few studies address the qualification of the SHM system performances, thus limiting the transition of SHM from research to field implementation. For this reason, the paper presents a model-assisted framework for SHM performance prediction based on virtual tests. The approach has been developed for the real-time detection of fatigue crack growth and has been verified on a full-scale fatigue test of an aeronautical stiffened structure. The availability of a calibrated and validated numerical finite element model of the structure allows the estimation of strain dependent feature sensitivity to damage. In particular, a database of virtual fatigue crack propagation tests has been used to predict the diagnostic system performances in a model-assisted framework, thus calculating the minimum detectable crack length for a specified level of probability of detection and confidence and probability of false alarms. The methodology has been verified using a real-time SHM system based on a fiber Bragg grating sensor network for the strain measure and a widely recognised statistical method based on outlier analysis for damage detection, specifically consisting on the calculation of the Mahalanobis distance from a baseline condition. The sensor network has been installed on the stringers of a helicopter tail boom subject to fatigue load and the real-time strain signals are used to detect fatigue damages based on the strain field modifications. Eventually, the performance of the monitoring system has been experimentally verified against the predicted performance of the model-assisted methodology.

Paper

Authors

Sbarufatti, Claudio*Corbetta, MatteoSan Millán, JavierFrövel, MalteStefaniuk, MichalGiglio, Marco*Contact