AUTONOMOUS STRUCTURAL HEALTH MONITORING—PART I: MODAL PARAMETER ESTIMATION AND TRACKING

A growing interest for techniques and systems allowing the early detection and monitoring of damage based on vibration analysis is clearly present in different research and application areas, such as civil constructions, mechanical systems, and aircraft and aerospace industry. However, an important element for the applicability of modal-based damage assessment techniques in practice is the automation of the identification and tracking procedure. In this contribution it is shown that, by using a frequency-domain maximum likelihood estimator, features such as high accuracy and confidence bounds for the estimated parameters and robustness for high measurement noise levels create the possibility to automate the modal identification process. For the validation of the model, criteria based on a statistical approach were developed in addition to the well-known criteria such as modal phase colinearity and mode complexity, while the final mode selection is done by means of a fuzzy clustering algorithm. At the same time, an accurate mode-tracking algorithm is presented. It is shown that the problem of coinciding poles, due to shifting or crossing modes under changing structural dynamics, can hamper the mode tracking and a robust solution is proposed. The possibilities and limitations of the automated approach are investigated and tested for a slat track of an Airbus A320 commercial airplane, providing a preliminary study for future monitoring practices during life cycle tests on slat tracks.