Recently, features and techniques from speech processing have started to gain increasing attention in the Structural Health Monitoring (SHM) community, in the context of vibration analysis. In particular, the Cepstral Coefficients (CCs) proved to be apt in discerning the response of a damaged structure with respect to a given undamaged baseline. Previous works relied on the Mel-Frequency Cepstral Coefficients (MFCCs). This approach, while efficient and still very common in applications, such as speech and speaker recognition, has been followed by other more advanced and competitive techniques for the same aims. The Teager-Kaiser Energy Cepstral Coefficients (TECCs) is one of these alternatives. These features are very closely related to MFCCs, but provide interesting and useful additional values, such as e.g., improved robustness with respect to noise. The goal of this paper is to introduce the use of TECCs for damage detection purposes, by highlighting their competitiveness with closely related features. Promising results from both numerical and experimental data were obtained.

A framework for numerically predicting the wind-excited response of suspension bridges with a certain level of confidence is established by means of output only system identification, model updating, wind-response simulation, and input-output comparison. A real case study represented by the identification and analysis of a newly built suspension bridge is considered. In system identification, the estimates of the modal parameters of the structure are provided with uncertainty bounds that take into account variations in identified modal features arising from different selections of the main parameters in the implementation of the identification technique. Based on the identified modal parameters, a finite-element model of the bridge is updated via an optimization technique. The updated model is then employed for numerically predicting the wind-excited structural response. Comparison with recorded data allows to check the accuracy of the model’s predictions as well as to indicate possible strategies for ref...

Accurate thermal properties are crucial for modeling the response of infrastructure to fire scenarios. While other researchers have contributed significant effort toward characterizing the thermal behavior of parallel-wire structural cable stays, no method has been derived explicitly for suspension bridge main cables, which are typically two orders of magnitude larger in cross section. These cables cannot be treated as monolithic steel sections due to the nature of their composition, and their thermal behavior is greatly influenced by voids and point contacts between their constituent cylindrical wires. This study derives the first empirically driven estimation of the effective bulk thermal conductivity of suspension bridge main cables using the data collected from thermal experimentation on a full-scale mock-up of the main cable panel (approximately 10,000 wires, 52 cm diameter, 6 m long) and gradient-based optimization of a representative finite-element model. Results show that the effective thermal conductivity of suspension bridge main cables is more than an order of magnitude smaller in the radial direction than in the axial direction and that the effective radial conductivity is an order of magnitude smaller than previous theoretical estimates have predicted. The resulting bulk conductivity serves as a useful tool for engineers and researchers because it allows a large, thermally complex geometry to be modeled as a simple monolith with orthotropic thermal conductivity properties.