The average vibro-acoustic performance of a junction between two-dimensional structural elements is often quantified by its diffuse vibration reduction index, especially for building structures. Existing prediction methods either assume an infinite junction length or consider non-diffuse transmission. In this work an approach for predicting the diffuse vibration reduction index of finite junctions of arbitrary complexity is developed. First, the mean and (co)variance of the diffuse coupling loss factor of a finite junction are obtained within the hybrid deterministic-statistical energy analysis framework. Dedicated basis functions are proposed to efficiently describe the interface displacements of the diffuse subsystems. Subsequently, the relation between the mean vibration reduction index and the coupling loss factor is established. It is demonstrated that this relation involves both the mean and the variance of the coupling loss factor. Additionally, the relation between the variance of the vibration reduction index and the (co)variances of the coupling loss factors is derived. Finally, the proposed approach is both numerically validated and compared to experimental results for several finite junctions between building elements, which are modelled as plates. For the numerical validation, the results obtained with the proposed approach are compared with those of an ensemble of junctions with the same bare structure but with point masses attached at random locations on the walls and floors. The validations demonstrate that an accurate prediction of the mean and variance of the diffuse vibration reduction index is possible when the uncertainty across the random ensemble is sufficiently large. The comparison to experimental results involves T and X junctions between directly coupled plates. At low and medium frequencies, the experimental data are well captured within the 95% confidence interval of the hybrid model results. At high frequencies, the uncertainty on the hybrid results is very small; such differences with the experimental data are caused by modelling errors.
Structural health monitoring relies on the repeated observation of damage-sensitive features such as strains or natural frequencies. A major problem is that regular changes in temperature, relative humidity, operational loading, and so on also influence those features. This influence is in general nonlinear and it affects different features in a different way. In this article, an improved technique based on kernel principal component analysis is developed for eliminating environmental and operational influences. It enables the estimation of a general nonlinear system model in a computationally very efficient way. The technique is output-only, which implies that only the damage-sensitive features need to be measured, not the environmental parameters. The nonlinear output-only model is identified by fitting it to the damage-sensitive features during a phase in which the structure is undamaged. Afterwards, the structure is monitored by comparing the model predictions with the observed features. The technique is validated with natural frequency data from a three-span prestressed concrete bridge, which was progressively damaged at the end of a one-year monitoring period. It is demonstrated that capturing the regular variations of the features requires a nonlinear model. Monitoring the misfit between the predictions made with this model and the observed data allows a very clear discrimination between validation data in undamaged and damaged conditions.
Structural Health Monitoring (SHM) and Experimental Modal Analysis (EMA) have revealed to be really efficient tools for the damage detection of structures and structural elements in many engineering fields ( Shock Vib. Dig . 1998; 30 (2):91–105; Philos. Trans. R. Soc. A 2007; 365 (1851):303–315; Mech. Syst. Signal Process. 2003; 17 (1):133–142; Philos. Trans. R. Soc. : Math. Phys. Eng. Sci. 2001; 359 (1778): 131–149; Struct. Control Health Monit. 2006; 14 :1083–1100; Mech. Syst. Signal Process. 2004; 17 (1): 83–89). Unfortunately the great variety of morphologies, construction materials and structural schemes makes these techniques not easily applicable to buildings, due to inherent problems related to the location and the extent of damage, the sensitivity of the dynamic response to damage, the choice of damage indexes to be used, the sensors' location, etc. On the other hand, the modern seismic capacity design of buildings in earthquake‐prone areas tends to locate dissipative zones in well‐determined portions of structures (CEN, European Committee for Standardization, EN 1998‐1. Eurocode 8 : Design of Structures for Earthquake Resistance. Part 1 : General Rules, Seismic Actions and Rules for Buildings , European Community, Brussels, Belgium, 2005); thus, the application of vibration‐based damage detection techniques to earthquake‐resistant structures seems to be very promising even if nowadays there are only few studies on these arguments. The present paper reports the experiences of a vibration‐based damage identification study applied to a steel–concrete composite frame structure, suitably designed to be high ductile according to Eurocode 8 and localizing the seismic energy dissipation in the beam‐to‐column joints. The structure was subjected to series of pseudo‐dynamic (PsD) and cyclic tests with increasing peak ground acceleration at the European Laboratory for Structural Assessment of Joint Research Centre at Ispra (VA, Italy). The damaging phenomena, caused by PsD tests, were assessed and quantified by means of a multi‐level vibration‐based approach suitably designed in order to evaluate the changes in the global dynamic structural response and to experimentally estimate the reduction in joint stiffness. Copyright © 2008 John Wiley & Sons, Ltd.
No abstract is provided for this article.
Reinforcement corrosion is a major issue in reinforced concrete structures with severe societal and economic consequences if not detected and treated in time. This paper presents an elaborate experimental study to effectively monitor chloride-induced corrosion damage in reinforced concrete beams. A combined method of acoustic emission sensing and vibration-based monitoring is developed to detect, characterise and localise damage. Additionally, crack measurements on the concrete surface are performed as a reference technique. Four beams are corroded with an accelerated corrosion set-up while two additional beams are used as reference specimens. Whereas these monitoring techniques have already been applied individually to assess corrosion in reinforced concrete beams, they are here combined, in order to verify their complementarity. This results in an elaborate and innovative data-set which allows us to draw new conclusions on the way the techniques provide information on the evolution of corrosion damage in time and space. It was found that acoustic emission sensing can accurately detect and localise damage before cracking of the concrete, especially after dedicated noise filtering through clustering of the AE signals. Vibration-based monitoring is less sensitive to early damage, yet natural frequencies contain absolute information about the stiffness decrease due to corrosion damage, and strain mode shapes can localise damage on a larger scale. In addition, results from both techniques are in line with the crack measurements. As a result, the combination of these various monitoring methods offers valuable and complementary insights about the corrosion process.
No abstract is provided for this article.
Predicting the airborne sound insulation of a complex building element generally requires a detailed model of that element, as simplified analytical models such as an equivalent orthotropic plate are only accurate for the first few natural frequencies. A commonly adopted strategy therefore consists of constructing a detailed finite element model and computing the expected value of the sound reduction index by numerically integrating the plane-wave transmission over all angles of incidence. This is not only computationally costly, but all information on the uncertainty of the predicted values due to the statistical nature of the diffuse field assumption for the rooms is also lost. In this work, an alternative method is therefore proposed, where a finite element model of a building element is coupled to statistical energy analysis models of the rooms. Both the mean and variance of the sound reduction index are computed, so that the uncertainty of the predicted values due to the generalized diffuse field assumption can be assessed. The method is then applied to the sound reduction index prediction of a rib-stiffened plate and a thicker masonry wall and validated against measured data. It is found that the proposed approach can capture both the complex dynamics of the walls and the uncertainty of the generalized diffuse field assumption of the rooms.
No abstract is provided for this article.
Vibration-based damage identification can constitute a successful approach for Structural Health Monitoring (SHM) of civil structures. It is a non-destructive condition assessment method, dependent on the identification of changes in the modal characteristics of a structure that are related to damage. However, the damage identification from the modal characteristics of existing structures currently suffers from a low sensitivity of eigenfrequencies and mode shapes to certain types of damage. Furthermore, the sensitivity of eigenfrequencies to environmental influences may be sufficiently high to completely mask the effect even of severe damage. Modal strains and curvatures are more sensitive to local damage, but the direct monitoring of these quantities is challenging when the strain level is very low. In the present work, the identification of the modal strains of a pre-stressed concrete beam, subjected to a progressive damage test, is performed. Dynamic measurements are conducted on the beam at the beginning of each cycle and its response is recorded with multiplexed Fiber-optic Bragg Grating (FBG) strain sensors. Bending, lateral and torsional modes are accurately identified from dynamic strains of the sub-microstrain level. The evolution of the modal characteristics of the beam after each loading cycle is investigated. Changes of the eigenfrequency values, the amplitude and the curvature of the strain mode shapes are observed. The changes in the strain mode shapes appear at the locations where the damage is induced, and are already identified from an early damaged state.
Offshore wind turbines are exposed to continuous wind and wave excitation. The continuous monitoring of high periodic strains at critical locations is important to assess the remaining lifetime of the structure. Some of the critical locations are not accessible for direct strain measurements, e.g. at the mud-line, 30 meter below the water level. Response estimation techniques can then be used to estimate the response at unmeasured locations from a limited set of response measurements and a system model. This paper shows the application of a Kalman filtering algorithm for the estimation of strains in the tower of an offshore monopile wind turbine in the Belgian North Sea. The algorithm makes use of a model of the structure and a limited number of response measurements for the prediction of the strain responses. It is shown that the Kalman filter algorithm is able to account for the different types of excitation acting on the structure in operational conditions, in this way yielding accurate strain estimates that can be used for continuous fatigue assessment of the wind turbine.
Preservation of architectural heritage is considered a fundamental issue in the cultural life of modern societies. In addition to their historical interest, monuments significantly contribute to the economy of cities and countries by providing key attractions. In this context, structural damage identification at an early stage plays an important role in heritage preservation. Dynamic based methods to assess the damage are attractive tools for this type of structure because they are non-destructive and are able to capture the global structural behavior. The present paper aims at exploring damage in masonry structures at an early stage by vibration measurements. For this purpose, an approach is presented based of dynamic damage identification methods. To evaluate the approach a one arch model was constructed in the laboratory. Afterwards, progressive damage was induced in the arch and sequential modal identification analysis was performed at each damage stage, aiming at finding adequate correspondence between dynamic behavior and internal crack growth. Comparisons between different techniques were made to evaluate which method is more adequate to identify damage in masonry constructions. The dynamic based methods allowed detecting and locating the damage in the specimens.
