Autonomous Health Monitoring of Composite Structures Using a Statistical Damage Index Approach

摘要

This paper is concerned with the detection and characterization of impact damage in stiffened composite structures using high frequency Lamb waves and low frequency modal vibrations. The geometric and material complexities of the structure present practical difficulties in the direct analysis of both wave propagation and modal vibration data using theoretical constructs. An improved test setup, consisting of high fidelity sensor arrays, laser scanning vibrometer, data acquisition boards, signal conditioning and dedicated software has been implemented. The conceptual structural health monitoring (SHM) system presented here involves a low level computational effort, has high reliability, and is able to treat the acquired data in real-time to identify the presence of existing as well as emerging damage in the structure. A statistical damage index algorithm is developed and automated by utilizing a diagnostic imaging tool to identify a defect right from its appearance, with high degree of confidence. The main advantage of the method 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 feasibility of developing a practical Intelligent Structural Health Monitoring (ISHM) System, based on the concept of "a structure requesting service when needed," is discussed.