In this paper, we present two novel algorithms to realize a finite dimensional, linear time-invariant state-space model from input-output data. The algorithms have a number of common features. They are classified as one of the subspace model identification schemes, in that a major part of the identification problem consists of calculating specially structured subspaces of spaces defined by the input-output data. This structure is then exploited in the calculation of a realization. Another common feature is their algorithmic organization: an RQ factorization followed by a singular value decomposition and the solution of an overdetermined set (or sets) of equations. The schemes assume that the underlying system has an output-error structure and that a measurable input sequence is available. The latter characteristic indicates that both schemes are versions of the MIMO Output-Error State Space model identification (MOESP) approach. The first algorithm is denoted in particular as the (elementary MOESP scheme)...

Subspace model identification-Part 1. The output-error state-space model identification class of algorithms

In this paper, the use of the combined deterministic-stochastic subspace identification algorithm for the experimental modal analysis of mechanical structures is discussed. The algorithm requires artificial forces to be applied to the structure, so it can be used for experimental modal analysis (EMA). The algorithm can also be used for operational modal analysis (OMA), since the excitation level of the artificial force(s) can be low compared to the excitation level of the ambient forces. Both the modes that are artificially excited and those that are excited by the ambient forces are identified. This type of operational modal analysis is called an OMAX analysis (Operational Modal Analysis with eXogenous inputs) [1]. The main advantages of OMAX over OMA are that the modes that are excited by the artificial forces can be scaled to unity modal mass and that a higher number of modes can be identified.

Reference-based combined deterministic-stochastic subspace identification for experimental and operational modal analysis

State-of-the-art on strengthening of masonry structures with textile reinforced mortar (TRM)

Damage and performance evaluation of masonry churches in the 2009 L’Aquila earthquake

The importance of wireless sensor networks in structural health monitoring is unceasingly growing, because of the increasing demand for both safety and security in the cities. The speedy growth of ...

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Wireless sensor network for structural health monitoring: A contemporary review of technologies, challenges, and future direction:

Knowledge of the dynamic behavior of complex buildings subjected to near-fault earthquakes may be enriched by valuable information obtained through rapid onsite dynamic testing to aid in the design of appropriate retrofitting interventions. Through a case study, the article demonstrates the enhancement in comprehension of the structural behavior obtained by means of a 2-day testing campaign conducted on a complex building of the Engineering Faculty, Edifice A, which was heavily damaged in the 2009 L'Aquila earthquake. The onsite testing was carried out with a network of 13 accelerometers opportunely located to identify the dynamic characteristics of the structure by means of ambient noise-induced vibration. Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (SSI) output-only procedures were both used to identify the main modal parameters of two substructures of the building. The modal characteristics were used to update a finite element model representing small amplitude vibrations of the damaged structures. The direct comparison of the identified modal features with finite element models, in which damaged member locations are determined by onsite visual observations, has permitted identification of a model representative of the structural behavior of the building in the immediate postearthquake conditions.

Output‐Only Identification and Model Updating by Dynamic Testing in Unfavorable Conditions of a Seismically Damaged Building

Structural performance of the historic and modern buildings of the University of L’Aquila during the seismic events of April 2009☆

The work presents the inter-disciplinary multi-year project focused on the permanent seismic monitoring of a historical structure, the Basilica S. Maria di Collemaggio, by means of an advanced wireless sensor network. Considered among the architectural masterpieces of the Italian Romanesque, the structural behaviour of the monumental masonry church is strongly debated after the heavy damages and the partial collapse that occurred during the 2009 L’Aquila earthquake. From the perspective of information technology, critical issues in the wireless data acquisition and communication are analysed. The sensor network design, deployment and performance are discussed with respect to the high-demanding service requirements—as well as the non-negligible management costs—specifically related to the long-term monitoring of a monumental masonry structure in a seismic area. From the perspective of experimental signal analysis, the acceleration data collected during a 3-year period of seismic monitoring are analysed in the frequency and time domains. The results allow the clear detection of complex interactions between the masonry structures and some of the temporary protective installations. Stochastic subspace identification procedures are applied, with critical analysis of their effectiveness in the assessment of reliable modal models from the building response to real seismic events. Finally, the robustness of the modal identification obtained from the structural responses to different near- and far-field micro-earthquakes is discussed, with the aid of numerical models of the damaged and protected church configuration.

Long-term structural monitoring of the damaged Basilica S. Maria di Collemaggio through a low-cost wireless sensor network

The research proposes the combined use of a Glass Fiber Reinforced Cement Matrix (GFRCM) composite with an integrated fiber optic sensing system for innovative seismic retrofitting of masonry vaults. The need of eco-compatibility of bonding material with masonry support implies the use of Hydraulic Lime Mortar (HLM) as bonding matrix that, in contrast, is characterized by lower adhesion capacity respect to polymeric resins and not well-known carrying-load properties. Hence, monitoring of the operating features of the GFRCM reinforcement has been pursued with an advanced fiber optic sensing system realized through Fiber Bragg Grating (FBG) sensors. The use of FBG sensors is justified by a large number of advantages such as small sensor dimensions, low weight as well as high static and dynamic resolution of measured values, distributed sensing feature allowing to detect anomalies in load transfer between reinforcement and substrate. Specifically, the proposed retrofitting and monitoring technique is designed and applied to an old masonry pavilion vault. A nonlinear finite element model of the reinforced structure is developed in order to quantify the effectiveness of the GFRCM strengthening layer and to derive the convenient position of the optic fibers for a correct monitoring of the reinforced vault. An experimental campaign is carried out in order to verify the proper behavior of the proposed strengthening and sensing strategy.

Effective seismic strengthening and monitoring of a masonry vault by using Glass Fiber Reinforced Cementitious Matrix with embedded Fiber Bragg Grating sensors

Francesco Potenza

Papers

Output‐Only Identification and Model Updating by Dynamic Testing in Unfavorable Conditions of a Seismically Damaged Building

Structural performance of the historic and modern buildings of the University of L’Aquila during the seismic events of April 2009☆

Long-term structural monitoring of the damaged Basilica S. Maria di Collemaggio through a low-cost wireless sensor network

Effective seismic strengthening and monitoring of a masonry vault by using Glass Fiber Reinforced Cementitious Matrix with embedded Fiber Bragg Grating sensors

Prediction of the fundamental frequencies and modal shapes of historic masonry towers by empirical equations based on experimental data