A wireless fatigue monitoring system combined with innovative dam | 2375
Journal of Aeronautics & Aerospace Engineering

Journal of Aeronautics & Aerospace Engineering
Open Access

ISSN: 2168-9792


A wireless fatigue monitoring system combined with innovative damage estimation algorithm

2nd International Conference and Exhibition on Mechanical & Aerospace Engineering

September 08-10, 2014 Philadelphia, USA

Xuan Li

Posters: J Aeronaut Aerospace Eng

Abstract :

Fatigue has long been a threatening issue for critical structures such as aircraft and railway system, which makes the on-line fatigue monitoring especially essential for these components. In this paper, we have developed an in-situ wireless real-time fatigue monitoring system which could provide instant feedback as well as precise fatigue estimation. In this system, the Rainflow counting (RFC) method is adopted as the core algorithm which quantifies fatigue damages, and Digital Signal Processing (DSP) is embedded as the core module for data collection and analysis. With strain gauge and Polyvinylidene Fluoride (PVDF) sensors, our system could record the strain history of certain structures and provide a quick update of fatigue estimation. In addition, a damage estimation algorithm using Kalman filter has been attached to our system. This algorithm could realize full-scale strain monitoring of structures with data from limited positions. The accuracy of the system and algorithm has been examined with a truss structure under laboratory conditions. With the merits of low cost, high accuracy and great reliability, we believe this wireless fatigue sensing system could be further applied in aerospace engineering, mechanical engineering, civil infrastructures, etc.

Biography :

Xuan Li is currently pursuing his MD at Dalian University of Technology. He also works as a research assistant in the Key laboratory of structural monitoring and control for civil infrastructures of Liaoning Province. With several papers published, he has been devoted in the research of Structural Health Monitoring (SHM) covering wireless sensing system, data mining and sensor optimized placement.