The present paper aims at damage assessment of masonry structures in an early stage. Two replicates of historical constructions were built in virgin state, one arch with 1.5 m span and one shear wall of 1 m. Afterwards, progressive damage was applied and sequential modal identification analysis was performed in each damage stage, aiming at finding adequate relations between changes in dynamical behaviour and internal crack growth. During the dynamic tests, accelerations and strains were recorded in many points of the replicates. Comparisons between different techniques based on vibrations measurements were made to evaluate which methods are the most suitable for identifying damage in masonry constructions.
As part of the Brite-EuRam project BE96-3157 SIMCES (System Identification to Monitor Civil Engineering Structures) the three span box bridge Z24 in Switzerland was monitored during almost one year before it was artificially damaged. In the preceding monitoring period the influence of environmental conditions, such as humidity, wind and especially temperature, on the bridge eigenfrequencies was studied. The goal of the subsequent damage tests, corresponding to realistic and relevant cases, was to prove that damage could be detected, localised and quantified by considering changes in eigenfrequencies and modeshapes. Some of the main conclusions are that ambient vibrations treated by proper system identifications algorithms can provide accurate results for eigenfrequencies and modeshapes, that it is mandatory to filter beforehand the influence of environmental conditions and that small, stiffness degradation producing damage can be detected if the corresponding eigenfrequency diminutions surpass 1%.
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Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.
For slender and lightweight structures, vibration serviceability is a matter of growing concern, often constituting the critical design requirement. With designs governed by the dynamic performance under human-induced loads, a strong demand exists for the verification and refinement of currently available load models. The present contribution uses a 3D inertial motion tracking technique for the characterization of the in-field pedestrian behavior. The technique is first tested in laboratory experiments with simultaneous registration of the corresponding ground reaction forces. The experiments include walking persons as well as rhythmical human activities such as jumping and bobbing. It is shown that the registered motion allows for the identification of the time variant pacing rate of the activity. Together with the weight of the person and the application of generalized force models available in literature, the identified time-variant pacing rate allows to characterize the human-induced loads. In addition, time synchronization among the wireless motion trackers allows identifying the synchronization rate among the participants. Subsequently, the technique is used on a real footbridge where both the motion of the persons and the induced structural vibrations are registered. It is shown how the characterized in-field pedestrian behavior can be applied to simulate the induced structural response. It is demonstrated that the in situ identified pacing rate and synchronization rate constitute an essential input for the simulation and verification of the human-induced loads. The main potential applications of the proposed methodology are the estimation of human-structure interaction phenomena and the development of suitable models for the correlation among pedestrians in real traffic conditions.
No abstract is provided for this article.
Vibration monitoring of civil engineering structures has gained a lot of interest over the past few years, due to the relative ease of instrumentation and the development of new powerful system identification techniques. The damage assessment step consists of relating the dynamic characteristics to a damage pattern of the structure. The presented technique makes use of the calculation of modal bending moments and curvatures to derive the bending stiffness at each location. The basic assumption is that damage can be directly related to a decrease of stiffness in the structure. Eigenfrequencies are sensitive damage indicators. Modal curvatures seem to be more sensitive to local damage than the modal displacements. The technique is validated on a reinforced concrete beam, which is gradually damaged and is instrumented with accelerometers, displacement transducers and strain gauges.
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No abstract is provided for this article.
No abstract is provided for this article.
In the framework of developing a non-destructive vibration testing method for monitoring the structural integrity of constructions in civil engineering, it is important to be able to determine the dynamic stiffness in each section of the structure from measured modal characteristics. From the dynamic stiffnesses, one obtains directly an idea of the extension of the cracked zones in the structure. In an experimental program, a concrete beam of 6 meter length is subjected to an increasing static load to introduce cracks. After each static preload the beam is tested dynamically in a free-free set-up. The change in modal parameters is then translated into damage in the beam. The technique to predict the damage location and intensity that will be presented in the paper, is a direct stiffness derivation from measured modal displacement derivatives. Using the bending modes, the dynamic bending stiffness can be derived from modal curvatures. Using the torsional modes, the dynamic torsion stiffness can be derived from modal torsion rates.
