Key Engineering Materials Vols. 569-570

Abstract: Current maintenance of concrete civil infrastructure such as buildings, bridges, dams and highways, is based on scheduled inspection consisting in visual and/or local inspection techniques (i.e. acoustic/ultrasonic methods, radiography, eddy-current methods). A major trend in the field is the development of automated on-line monitoring systems. The current study is focused on the use of ultrasonic wave propagation techniques based on embedded piezoelectric transducers for the on-line monitoring of the damage state in concrete. The technique is based on the use of an ultrasonic emitter-receiver pair and the construction of a damage indicator focused on the early wave arrival. The proposed simple monitoring system is implemented during several pull-out tests on concrete blocks. The results demonstrate the excellent performance of the system which is able to detect the initiation and follow the evolution of the cracking until complete failure.

Abstract: This paper illustrates an application of Bayesian logic to monitoring data analysis and structural condition state inference. The case study is a 260 m long cable-stayed bridge spanning the Adige River 10 km north of the town of Trento, Italy. This is a statically indeterminate structure, having a composite steel-concrete deck, supported by 12 stay cables. Structural redundancy, possible relaxation losses and an as-built condition differing from design, suggest that long-term load redistribution between cables can be expected. To monitor load redistribution, the owner decided to install a monitoring system which combines built-on-site elasto-magnetic and fiber-optic sensors. In this note, we discuss a rational way to improve the accuracy of the load estimate from the EM sensors taking advantage of the FOS information. More specifically, we use a multi-sensor Bayesian data fusion approach which combines the information from the two sensing systems with the prior knowledge, including design information and the outcomes of laboratory calibration. Using the data acquired to date, we demonstrate that combining the two measurements allows a more accurate estimate of the cable load, to better than 50 kN.

Abstract: A substructural damage identification approach based on structural response reconstruction in frequency domain is presented. The response reconstruction is based on transforming the measured responses into responses at other locations with the transmissibility matrix and then the relationship between two sets of response vectors is formulated. The damage identification is conducted by minimizing the difference between a measured response vector and the reconstructed response vector. Measured acceleration responses from the damaged substructure and the finite element model of the intact substructure only are required in the identification algorithm. A dynamic response sensitivity-based method with the adaptive Tikhonov regularization technique is adopted for the damage identification with improved results from noisy measurements. A seven-storey frame structure is taken as an example to illustrate the effectiveness and performance of the proposed approach.

Abstract: The response sensitivity-based method for damage detection is integrated with the singular spectrum analysis (SSA) technique for an improvement of the identification results. The measured response of the structure is SSA decomposed, and the response sensitivity matrix as well as the computed response vectors are projected into the corresponding decomposition subspace to form the identification equations, and components containing the least measurement noise and most damage information can be selected to detect local damages in the structure. The proposed integrated approach is illustrated with a planar truss structure with discussions on the effectiveness of a single and multiple decomposed component of the measured response in the damage detection.

Abstract: This paper presents a two-stage scheme of damage identification for plate-type structure. In the first stage, probable damaged regions and their relative severities can be detected based on lock-in thermography technique. In the second stage, the relation between the damage level and its corresponding natural frequencies of the plate is constructed by means of Kriging surrogate model based on dynamic analysis. The inverse problem of damage quantification over the surrogate model is then solved by using a robust stochastic particle swarm optimization algorithm. Experimental study on a double-damaged plate demonstrates the feasibility and effectiveness of the proposed scheme.

Abstract: This work constitutes a damage detection study of a glass plate using the statistical approach of outlier analysis, which is also referred to here as novelty detection. A glass plate instrumented with low-profile, surface-bonded transducers is used in the investigation. Ultrasonic Lamb waves are applied for detecting various crack length on the same plate. The study reveals a distinction between the damage and undamaged plate, and also assesses the severity of damage.

Abstract: In this paper, the possibility and validity of damage detection based on velocity response of a simply supported beam under the moving load are examined theoretically and numerically. It includes the following parts: First, the theoretic background of the beam vibration subjecting to moving load is briefly described. And then, the velocity responses of a simple supported beam are calculated by software Ansys. Using wavelet transform, the damage location can be identified successfully. At last, the effects of noise and load speed are discussed in detail. Numerical studies show the validity of the proposed method and a good noise tolerance using the velocity response.

Abstract: This paper presents a vibration based procedure for locating reductions of stiffness in two-dimensional structures that can be modeled as plates. This procedure is a generalization to the two-dimensional case of the previously published Interpolation Damage Detection Method (IDDM). The method is based on the definition of a damage sensitive feature in terms of the accuracy of a spline function in interpolating the operational displacement shapes of the structure. These latter are recovered from frequency response functions (FRFs) measured at different locations of the structure during vibrations. At the i-th location, the FRF is calculated through spline interpolation using the FRF’s recorded at the all the instrumented locations but the i-th. For two-dimensional structures a spline surface is defined to interpolate the operational shapes. The accuracy of the spline interpolation is measured by an error function defined as the difference between the measured and interpolated operational mode shapes. At a certain location an increase (statistically meaningful) of the interpolation error, with respect to a reference configuration, points out a localized variation of the operational shapes thus revealing the existence of damage. The two dimensional IDDM algorithm is checked herein through numerical simulations, using the FE model of a plate and modeling local reductions of stiffness through a reduction of the elastic modulus of the material of one or more elements of the model.

Abstract: Modal filtration in the field of damage detection has many advantages, including: its autonomous operation (without the interaction of qualified staff), low computational cost and low sensitivity to changes in external conditions. However, the main drawback of this group of damage detection methods is its limited applicability to operational data. The modal filtration of the responses spectra (in place of FRFs), proposed in the literature, often does not give the expected results, working properly only for excitation in the form of white noise, or an ideal impulse. In other cases, for example in rotational machines, when in the response spectrum the rotational velocity harmonics dominate it can give wrong results. For such cases authors propose to use a new type of spatial filter, similar to modal filter with the difference that it has ability to filter the operational deflection shape components from the system response. Its application together with classical modal filter allows for damage detection using operational data with other type of excitation. The main assumption of the new spatial filter is the orthogonality of the filter coefficient vector to the operational deflection shape vector, it is then similar to the classical modal filter.

Abstract: Structural damage identification is basically a nonlinear phenomenon; however, nonlinearprocedures are not used currently in practical applications due to the complexity and difficulty forimplementation of such techniques. Therefore, the development of techniques that consider the nonlinearbehavior of structures for damage detection is a research of major importance since nonlineardynamical effects can be erroneously treated as damage in the structure by classical metrics. Thispaper proposes the discrete-time Volterra series for modeling the nonlinear convolution between theinput and output signals in a benchmark nonlinear system. The prediction error of the model in anunknown structural condition is compared with the values of the reference structure in healthy conditionfor evaluating the method of damage detection. Since the Volterra series separate the responseof the system in linear and nonlinear contributions, these indexes are used to show the importanceof considering the nonlinear behavior of the structure. The paper concludes pointing out the mainadvantages and drawbacks of this damage detection methodology.