This is the story of a bell-tower and its monitoring. The Civic Tower in Portogruaro is a 59 m high masonry bell-tower, originally built in the XIII century, today leaning more than a meter out of plumb. Since 2003, the building inclination has been continuously monitored with an optical inclinometer in an effort to see whether the tilt is still in progress. When the monitoring started, it was thought highly unlikely that the Tower would tilt further. After three years of monitoring and historical investigation, this idea was completely overturned. We show here how the initial view developed to a final awareness via a probabilistic analysis of the information acquired, based on Bayesian logic. We illustrate how the joint use of instrumental monitoring and historical documentation allowed timely recognition of signs of ongoing tilting and accurate calculation not only of the mean inclination trend, but also the credibility of this information.
Bayesian analysis; real-time monitoring; historic building
Daniele Zonta: DICAM, University of Trento, via Mesiano 77, 38123 Trento, Italy
Matteo Pozzi:Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213-3890, USA
The electro-mechanical impedance (EMI) technique makes use of surface-bonded lead zirconate titanate (PZT) patches as impedance transducers measuring impedance variations monitored on host structural components. The present experimental work further evaluate an alternative to the conventional EMI technique which performs measurements of the variations in the output voltage of PZT transducers rather than computing electromechanical impedance (or admittance) itself. This paper further evaluates a variant of the EMI approach presented in a previous work of the present authors, suitable, for low-cost concrete structures monitoring applications making use of a credit card-sized Raspberry Pi single board computer as core hardware unit. This monitoring approach is also deployed by introducing a new damage identification index based on the ratio between the area of the 2-D error ellipse of specific probability of EMI-based measurements containment over that of the 2-D error circle of equivalent probability. Experimental results of damages occurring in concrete cubic and beam specimens are investigated under increasing loading conditions. Results illustrate that the proposed technique is an efficient approach for identification and early detection of damage in concrete structures.
Costas Providakis, Stavros Tsistrakis, Maristella Voutetaki, Maria Stavroulaki, John Agadakos, Eleftherios Kampianakis and George Pentes: School of Architectural Engineering, Technical University of Crete, GR-73100 Chania, Greece
Yiannis Tsompanakis: School of Environmental Engineering, Technical University of Crete, GR-73100 Chania, Greece
Corrosion of prestressed concrete structures is one of the main challenges that engineers face today. In response to this national need, this paper presents the results of a long-term project that aims at developing a structural health monitoring (SHM) technology for the nondestructive evaluation of prestressed structures. In this paper, the use of permanently installed low profile piezoelectric transducers (PZT) is proposed in order to record the acoustic emissions (AE) along the length of the strand. The results of an accelerated corrosion test are presented and k-means clustering is applied via principal component analysis (PCA) of AE features to provide an accurate diagnosis of the strand health. The proposed approach shows good correlation between acoustic emissions features and strand failure. Moreover, a clustering technique for the identification of false alarms is proposed.
corrosion; acoustic emission; principal component analysis; k-means method
Marianna Ercolino and Gennaro Magliulo: Department of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
Alireza Farhidzadeh: Mistras Group Inc., 195 Clarksville Rd, Princeton Junction, NJ 08550, USA
Gennaro Magliulo: Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin,
301 E Dean Keeton, C1748, Austin, TX, 78712, USA
This paper provides an overview of the use of different Distributed Optical Fiber Sensor systems (DOFSs) to perform Structural Health Monitoring (SHM) in the specific case of civil engineering structures. Nowadays, there are several methods available for extracting distributed measurements from optical fiber, and their use have to be according with the aims of the SHM performance. The continuous-in-space data is the common advantage of the different DOFSs over other conventional health monitoring systems and, depending on the particular characteristics of each DOFS, a global and/or local health structural evaluation is possible with different accuracy. Firstly, the fundamentals of different DOFSs and their principal advantages and disadvantages are presented. Then, laboratory and field tests using different DOFSs systems to measure strain in structural elements and civil structures are presented and discussed. Finally, based on the current applications, conclusions and future trends of DOFSs in SHM in civil structures are proposed.
structural health monitoring; distributed optical fiber; Brillouin and Rayleigh backscattering
Gerardo Rodríguez, Joan R. Casas and Sergi Villalba: UPC, Department of Construction Engineering, Technical University of Catalonia- BARCELONATECH,
Jordi Girona 1-3, 08034 Barcelona, Spain
This article identifies and addresses current limitations on the use of numerical models for validation and/or calibration of damage detection methodologies that are based on the analysis of the high frequency response of the structure to identify the occurrence of abrupt anomalies. Distributed-plasticity non-linear fiber-based models in combination with experimental data from a full-scale reinforced concrete column test are used to point out current modeling techniques limitations. It was found that the numerical model was capable of reproducing the global and local response of the structure at a wide range of inelastic demands, including the occurrences of rebar ruptures. However, when abrupt sudden damage occurs, like rebar fracture, a high frequency pulse is detected in the accelerations recorded in the structure that the numerical model is incapable of reproducing. Since the occurrence of such pulse is fundamental on the detection of damage, it is proposed to add this effect to the simulated response before it is used for validation purposes.
numerical models; damage detection; signal-processing; wavelets; reinforced concrete
Diego A. Aguirre: Department of Civil, Construction and Environmental Engineering, North Carolina State University,
Raleigh, NC 27695, USA
Luis A. Montejo:Department of Engineering Science and Materials, University of Puerto Rico at Mayaguez,
Mayaguez, PR 00680, Puerto Rico
Automated damage detection through Structural Health Monitoring (SHM) techniques has become an active area of research in the bridge engineering community but widespread implementation on in–service infrastructure still presents some challenges. In the meantime, visual inspection remains as the most common method for condition assessment even though collected information is highly subjective and certain types of damage can be overlooked by the inspector. In this article, a Frequency Response Functions–based model updating algorithm is evaluated using experimentally collected data from the University of Central Florida (UCF)–Benchmark Structure. A protocol for measurement selection and a regularization technique are presented in this work in order to provide the most well-conditioned model updating scenario for the target structure. The proposed technique is composed of two main stages. First, the initial finite element model (FEM) is calibrated through model updating so that it captures the dynamic signature of the UCF Benchmark Structure in its healthy condition. Second, based upon collected data from the damaged condition, the updating process is repeated on the baseline (healthy) FEM. The difference between the updated parameters from subsequent stages revealed both location and extent of damage in a
damage detection; dynamic nondestructive testing; bridges; frequency response functions; finite element models; model updating
Antonio Garcia-Palencia: HNTB Corporation, Boston, MA 02116, USA
Erin Santini-Bell: Department of Civil Engineering, University of New Hampshire, Durham, NH 03824, USA
Mustafa Gul: Department of Civil and Enviromental Engineering, University of Alberta, Edmonton, AB T6G 2W2, Canada
Necati Catbas: Department of Civil and Environmental and Construction Engineering, University of Central Florida,
Orlando, FL 32816, USA