Abstract
Many researchers have proposed vibration-based damage-detection approaches for continuous structural health monitoring. Translation to real applications is not always straightforward because the proposed methods have mostly been developed and validated in controlled environments, and they have not proven to be effective in detecting real damage when considering real scenarios in which environmental and operational variations are not controlled. This work was aimed to develop a fully-automated strategy to detect damage in operating tie-rods that only requires one sensor and that can be carried out without knowledge of physical variables, e.g., the axial load. This strategy was created by defining a damage feature based on tie-rod eigenfrequencies and developing a data-cleansing strategy that could significantly improve performance of outlier detection based on the Mahalanobis squared distance in real applications. Additionally, the majority of damage-detection algorithms presented in the literature related to structural health monitoring were validated in controlled environments considering simulated damage conditions. On the contrary, the approach proposed in this paper was shown to allow for the early detection of real damage associated with a corrosion attack under the effects of an intentionally uncontrolled environment.
Highlights
The development of automatic damage-detection strategies has played a key role in the condition-based maintenance of mechanical, civil and aerospace structures [1,2].Vibration-based damage identification approaches have been widely adopted for long-term continuous monitoring [3,4]
The authors of this work propose an automatic algorithm that can be used for the structural health monitoring of beam-like structures; this algorithm was validated with a one-of-a-kind application where real damage was detected on full-scale structural elements under the effects of an uncontrolled environment
We present an automatic data-cleansing procedure that was developed and successfully tested on long-term data acquired in an uncontrolled environment
Summary
The development of automatic damage-detection strategies has played a key role in the condition-based maintenance of mechanical, civil and aerospace structures [1,2].Vibration-based damage identification approaches have been widely adopted for long-term continuous monitoring [3,4]. The fundamental idea of these approaches is that damageinduced changes in physical properties (mass, damping and stiffness) are reflected in changes in modal parameters (eigenfrequencies, modal damping and mode shapes) [5,6]. According to this principle, modal parameters can be adopted to describe the state of health of a monitored structure and be used to define effective damage features. Many works in the literature have suggested strategies to overcome this limitation [10,11,12,13], but there have been few applications to structures under real operating conditions, especially when damage is present. The authors of this work propose an automatic algorithm that can be used for the structural health monitoring of beam-like structures; this algorithm was validated with a one-of-a-kind application where real damage was detected on full-scale structural elements under the effects of an uncontrolled environment
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