Ultrasonic wireless health monitoring system for near real-time damage identification of structural components

Abstract

This work aims at developing a compact and wireless structural health monitoring system (WSHM). The system samples ultrasonic wave propagation data, analyzes the collected data using a statistical damage index (SDI) approach and transmits the results to a remote location. The analysis provides an insight into the state of health of the structure under test as a function of time. The approach is designed to overcome the complexity and variability of the signals in the presence of damage as well as the geometric complexity of the structure, requiring minimal operator intervention. The approach establishes a baseline drawn from measurements done on an undamaged or partially damaged structure. This baseline is used to monitor for changes in the health of the structure. Damage indices are evaluated "instantly" by comparisons between the frequency response of the monitored structure and an unknown damage under the same ambient conditions. The approach is applied to identify several types of structural defects in steel girders and stiffened composite panels for different arrangements of the ultrasonic source and the ultrasonic receivers. The objectives are to deliver an early indication of the risk associated with the defect and to develop inspection and mitigation strategies to manage the risk using detailed, local, nondestructive evaluation of the areas identified with possible defects. The wireless data acquisition system and the automated data analysis tool developed under this work should improve the reliability of the defects detection capability and aid in the development of near real-time health monitoring systems for defects-critical structures.

Impact of Applied Loads on Guided Wave Structural Health Monitoring

“…The signal difference coefficient D of Eq. (2), along with other similar parameters, has frequently been proposed as a so-called "damage index" to track and quantify damage in structural components [10,11]. Just about any measure of signal differences is effective for damage detection when there are no other factors present that can change signals, such as variable loads or variations in other EOCs.…”