Papers by Keyword: Damage Localization

Abstract: Ultrasonic Lamb waves have gained popularity in non-destructive testing of plate-like structures due to their advantages such as low attenuation, high sensitivity, and wide detection range. This paper presents a novel baseline-free method for inspecting curved plate-like structures based on reciprocity loss. The method combines a modified damage imaging algorithm, a baseline-free detection method based on time reciprocity, and a calculation method for damage index values using the analysis of the focus position of time reciprocity signals. Experimental results demonstrate favorable effectiveness of the baseline-free method in detecting and locating multiple defects in the curved plate made of composite laminate.

Abstract: Load monitoring and damage identification are important tasks in the field of Structural Health Monitoring and are necessary for assessing the structural integrity and predicting the remaining useful life time. Reconstructing unknown force inputs or system parameters usually involves the solution of an inverse problem which is mostly ill-posed and therefore needs regularization. Using prior information about the desired values is advisable for obtaining meaningful solutions. Damages like for example cracks can often be interpreted as spatial singularities, which cause local stiffness reductions of the observed structures. Damage identification is the task of localizingand quantifying these stiffness reductions. On the other hand, unknown structure excitation usually has also some specia lcharacteristics which can be assumed as known apriori, e.g. spatial concentration for singular forces, short time duration for impact loads or narrow frequency bands for harmonic loads. In this case force reconstruction becomes also a localization and magnitude estimation problem. Thischaracteristic information is used to transform the inverse problem into a sparse recovery task. Inthe last years sparsity constrained regularization of inverse problem has attracted a lot of attention inapplied mathematics, especially in the context of compressive sensing.In this contribution it is shown how sparse solution techniques can be applied in monitoring sys-tems and how this will improve the reconstruction results and additionally reduce the number of required sensors.

Abstract: Using the static displacement data, this paper presented a damage localization method for a continuous beam. This method is based on the estimation of changes in the static displacements of the structure. The most significant advantage of the method is that it does not require development of an analytical model of the structure being tested. All predictions are made directly from the measurments taken on the structure. The efficiency of the proposed method is demonstrated using simulated data of a three-span continuous beam. The results showed that the region in which the displacement variation is maximum is the damaged region for the continuous beam. Regardless of damages being small or large, the proposed method can identify locations of structural damages accurately only using the displacement changes under the applied static load. The proposed procedure is economical for computation and simple to implement. The presented scheme may be useful for damage localization of the continuous beam.

Abstract: In order to develop a constitutive material model and to verify its consistency when implemented in a computational code, it is necessary to understand the material and to carry out a comprehensive experimental analysis. This can be a challenging task in the case of composite materials and structures, such as masonry, when using conventional measurements. Strain gauges and allow recording strains at a limited number of discrete points and do not provide sufficient amount of data, thus increasing the cost of the analysis. From that reason a full-field non-contact measurements, such as Digital Image Correlation (DIC), became very popular and valuable for analysis of structures subjected to mechanical loading and precise detection of the onset of strain localization. The presented study deals with tracking the strain localization using DIC in the case of masonry piers loaded by the combination of bending and compression. In such case the strain localizes into more compliant mortar joints while the complete collapse occurs when the masonry blocks fail to transfer tensile stress due to transversal expansion. The obtained data will be used for the validation of a finite element model to predict the behavior of masonry structures.

Abstract: This work focuses on the development of a damage localization tool using Topology Optimization(TO) as a solver for the inverse problem of localization. This approach is based on thecorrelation of a local stiffness loss and the change in frequencies due to damages. We use the loss instiffness for updating undamaged numerical models towards similar models with embedded damages.This work is an extension of past work and aims at increasing the detectability of the method usingusing aggregated Frequency Response Functions (FRFs) statistical criteria. Good results have finally been achieved for the localization of close damages by the Topology Optimization method.

Abstract: The number of vibration response sensors required for structural damage detection andprecise localization on a continuous structural topology is investigated. For damage detection thestate–of–the–art of vibration based methods need a required number of sensors q that may be “low”compared to the number of structural modes m, that is q << m. Yet, the opposite is generally suggestedfor precise damage localization, that is q > m. In this study the hypothesis that a “low” numberof vibration response sensors, q << m, may, under certain conditions, suffice for precise damage localization,is postulated. This hypothesis is “proven” experimentally by demonstrating that preciselocalization is indeed possible using a single vibration response sensor and an advanced StructuralHealth Monitoring methodology on a laboratory 3D truss structure.

Abstract: High energy consumption, excessive data storage and transfer requirements are prevailing issues associated with structural health monitoring (SHM) systems, especially with those employing wireless sensors. Data compression is one of the techniques being explored to mitigate the effects of these issues. Compressive sensing (CS) introduces a means of reproducing a signal with a much less number of samples than the Nyquist's rate, reducing the energy consumption, data storage and transfer cost. This paper explores the applicability of CS for SHM, in particular for damage detection and localization. CS is implemented in a simulated environment to compress SHM data. The reconstructed signal is verified for accuracy using structural response data obtained from a series of tests carried out on a reinforced concrete (RC) slab. Results show that the reconstruction was close, but not exact as a consequence of the noise associated with the responses. However, further analysis using the reconstructed signal provided successful damage detection and localization results, showing that although the reconstruction using CS is not exact, it is sufficient to provide the crucial information of the existence and location of damage.

Abstract: Cracking is a common type of failure in machines and structures. Cracks must be detected at an early stage before catastrophic failure. In structural health monitoring, changes in the vibration characteristics of the structure can be utilized in damage detection. A fatigue crack with alternating contact and non-contact phases results in a non-linear behaviour. This type of damage was simulated with a finite element model of a simply supported beam. The structure was monitored with a sensor array measuring transverse accelerations under random excitation. The objective was to determine the smallest crack length that can be detected. The effect of the sensor locations was also studied. Damage detection was performed using the generalized likelihood ratio test (GLRT) in time domain followed by principal component analysis (PCA). Extreme value statistics (EVS) were used for novelty detection. It was found that a crack in the bottom of the midspan could be detected once the crack length exceeded 10% of the beam height. The crack was correctly localized using the monitoring data.

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: In this study, a MFL (Magnetic Flux Leakage) based 3D inspection system which is incorporated into a cable climbing robot was investigated to monitor the healthy condition of steel cables. Firstly, a MFL sensor head prototype composed of two permanent magnets and eight hall sensors was designed and fabricated. A steel cable specimen with several types of damage, such as corrosion and cutting, was inflicted and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. The measured MFL signals were used to interpret the healthy condition of the steel cable. For improving the resolution and quantification of the damage level, digital signal processing techniques were performed. In addition, the measured MFL signals were visualized into a 3D MFL map for real-time and online cable monitoring. This visualized MFL map can provide the information about location, shape and size of damages very intuitively. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the MFL based cable inspection system.