A vibration-based approach for health monitoring of tie-rods under uncertain environmental conditions. (15th March 2022)

• Record Type: Journal Article
• Authors: Lucà, F.; Manzoni, S.; Cigada, A.; Frate, L.
• Is Part Of: Mechanical systems and signal processing. Volume 167:Part A(2022)
• Publication Date: 2022-03-15
• Subjects: Damage detection -- Tie-rod -- Structural health monitoring -- Operational modal analysis -- Continuous monitoring -- Statistical pattern recognition; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2021.108547
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: Damage indexes for tie-rod monitoring based on modal parameters and multivariate metric. Damage detection in tie-rods with no need of knowledge of axial load. Validation of the strategy on real tie-rods under realistic environmental conditions. Both the proposed damage indexes can detect damage in realistic environment. Abstract: This work proposes a vibration-based damage detection approach for axially loaded beam-type structures. The potential of the adopted approach is shown with an application to structural health monitoring of tie-rods: these elements, widely used in civil structures to balance horizontal forces in arches, are normally subject to a significant change of the axial load under environmental and operating conditions. The related changes in the modal parameters are usually greater than those caused by damage, at least at an early stage, making it hard to separate the different effects. In this work, the confounding effect of environmental factors is filtered out by considering more than one vibration mode at a time, thus framing damage detection as a multivariate outlier detection problem. Two damage indexes are presented, based on modal parameters (eigenfrequencies and mode shapes) and a multivariate metric (the Mahalanobis squared distance). The reasons behind the potential of the proposed framework are shown on simulated data first. Then, this strategy is validated on data coming from experimental tests, where two nominally identical tie-rods have been monitored for several months under the effects of realistic environmental and operational conditions. Both indexes proved to be weakly influenced by environmental variations, mainly related to temperature, and thus suitable for automatic damage detection.