Cecilia Surace

Mel-Frequency Cepstral Coefficients (MFCCs) have been proved to be via-ble to detect damage-induc...ed shifts in the frequency content of structures subjected to external forces. Nevertheless, the Melodic (Mel) Scale is a per-ceptual feature, roughly based on human perception and originally formulat-ed to resemble the biological mechanisms of the auditory apparatus. Thus, its straight application to non-auditive acquisition systems may be misleading.

One of the main problems concerning the field of Structural Health Monitoring (SHM) is the unavai...lability of data from different structural conditions. This is especially true for civil structures, where the collection of data from different damage states is often infeasible or economically inconvenient, particularly when dealing with architectural heritage structures.

This paper deals with a high-sensitivity method for the assessment of damage in high-strength fibres exposed to UV radiation. A recently developed experimental testing machine, based on an optical measurement system and electro-magnetic driving force, was used to characterize fibre materials. Stiffness, damping, and non-linearity were measured on several Kevlar® fibre samples previously exposed to UV light for different lengths of time. The results show that UV radiation increases the material non-linearity by amounts which can be clearly observed even at low vibration amplitudes.

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).

The identification of hysteretic degrading systems exposed to nonstationary loading is a paramount research topic, especially in the case of structures subjected to ground motion excitations. In this paper, the data recorded by a masonry building are used to detect the presence of seismic damage. To this aim, a parametric nonlinear identification is performed by adopting a Bouc– Wen-type multiple oscillator model. Starting from the results of the identification process, a damage index based on the degrading stiffness matrix is defined.