486,880 research outputs found
A new mechanical structural damage feature index based on HHT
A new damage feature index is presented for the structural health monitoring based on Hilbert-Huang transform (HHT). The energy marginal spectrum of the dynamic signal is used to construct damage characteristic parameter, which can reflect the signal energy variation and benefit the structural damage detection. A sinusoidal wave with frequency change and a composite plate vibration experiment with pre-defined damage are designed to verify the effectiveness of characteristic parameter in damage detection. Results obtained from simulation and test show that the extracted non-model-based damage feature index is available and sensitive in damage detection of time-varying system.Peer Reviewe
Underlying modal data issues for detecting damage in truss structures
Independent of the modal identification techniques employed for damage detection, use of measured modal data limits the expectations for damage location. These limitations are examined using the distribution of modal strain energy and the sensitivity of the frequency and mode shapes to structural stiffness changes. For given measured modal information of specific accuracy, this examination reveals the following: (1) damage detection is feasible for members that contribute significantly to the strain energy of the measured modes, (2) the modes which are most effective in detecting damage to certain critical members can be identified, and (3) a relationship can be drawn between the accuracy of the measured modes and frequencies and damage detection feasibility
Perturbation Analysis for Robust Damage Detection with Application to Multifunctional Aircraft Structures
The most widely known form of multifunctional aircraft structure is smart structures for structural health monitoring (SHM). The aim is to provide automated systems whose purposes are to identify and to characterize possible damage within structures by using a network of actuators and sensors. Unfortunately, environmental and operational variability render many of the proposed damage detection methods difficult to successfully be applied. In this paper, an original robust damage detection approach using output-only vibration data is proposed. It is based on independent component analysis and matrix perturbation analysis, where an analytical threshold is proposed to get rid of statistical assumptions usually performed in damage detection approach. The effectiveness of the proposed SHM method is demonstrated numerically using finite element simulations and experimentally through a conformal load-bearing antenna structure and composite plates instrumented with piezoelectric ceramic materials.FUI MSIE (Pole Astech
A method for vibration-based structural interrogation and health monitoring based on signal cross-correlation
Vibration-based structural interrogation and health monitoring is a field which is concerned with the estimation of the current state of a structure or a component from its vibration response with regards to its ability to perform its intended function appropriately. One way to approach this problem is through damage features extracted from the measured structural vibration response. This paper suggests to use a new concept for the purposes of vibration-based health monitoring. The correlation between two signals, an input and an output, measured on the structure is used to develop a damage indicator. The paper investigates the applicability of the signal cross-correlation and a nonlinear alternative, the average mutual information between the two signals, for the purposes of structural health monitoring and damage assessment. The suggested methodology is applied and demonstrated for delamination detection in a composite beam
Smart EMI monitoring of thin composite structures
This paper presents a structural health monitoring (SHM) method for in-situ damage detection and localization in carbon fibre reinforced plates (CFRP). The detection is
achieved using the electromechanical impedance (EMI) technique employing piezoelectric transducers as high-frequency modal sensors. Numerical simulations based on the finite element method are carried out so as to simulate more than a hundred damage scenarios. Damage metrics are then used to quantify and detect changes between the electromechanical impedance spectrum of a pristine and damaged structure. The localization process relies on artificial neural networks (ANN) whose inputs are derived from a principal component analysis of the damage metrics. It is shown that the resulting ANN can be used as a tool to predict the in-plane position of a single damage in a laminated composite plate
Principal component analysis and perturbation theory–based robust damage detection of multifunctional aircraft structure
A fundamental problem in structural damage detection is to define an efficient feature to calculate a damage index. Furthermore, due to perturbations from various sources, we also need to define a rigorous threshold whose overtaking indicates the presence of damages. In this article, we develop a robust damage detection methodology based on principal component analysis. We first present an original damage index based on projection of the separation matrix, and then, we drive a novel adaptive threshold that does not rely on statistical assumptions. This threshold is analytic, and it is based on matrix perturbation theory. The efficiency of the method is illustrated using simulations of a composite smart structure and experimental results performed on a conformal load-bearing antenna structure laboratory test
Nonlinear structural damage detection based on cascade of Hammerstein models
Structural damages can result in nonlinear dynamical signatures that can significantly enhance their detection. An original nonlinear damage detection approach is proposed that is based on a cascade of Hammerstein models representation of the structure. This model is estimated by means of the Exponential Sine Sweep Method from only one measurement. On the basis of this estimated model, the linear and nonlinear parts of the output are estimated, and two damage indexes (DIs) are proposed. The first DI is built as the ratio of the energy contained in the nonlinear part of an output versus the energy contained in its linear part. The second DI is the angle between the subspaces obtained from the nonlinear parts of two set of outputs after a principal component analysis. The sensitivity of the proposed DIs to the presence of damages as well as their robustness to noise are assessed numerically on spring-mass-damper structures and experimentally on actual composite plates with surface-mounted PZT-elements. Results demonstrate the effectiveness of the proposed method to detect a damage in nonlinear structures and in the presence of noise
Bridge damage detection based on vibration data: past and new developments
Overtime, bridge condition declines due to a number of degradation processes such as creep, corrosion, and cyclic loading, among others. Traditionally, vibration-based damage detection techniques in bridges have focused on monitoring changes to modal parameters. These techniques can often suffer to their sensitivity to changes in environmental and operational conditions, mistaking them as structural damage. Recent research has seen the emergence of more advanced computational techniques that not only allow the assessment of noisier and more complex data but also allow research to veer away from monitoring changes in modal parameters alone. This paper presents a review of the current state-of-the-art developments in vibration-based damage detection in small to medium span bridges with particular focus on the utilization of advanced computational methods that avoid traditional damage detection pitfalls. A case study based on the S101
bridge is also presented to test the damage sensitivity to a chosen methodology.Peer ReviewedPostprint (published version
Two-step Bayesian Structure Health Monitoring Approach for IASC-ASCE Phase II Simulated and Experimental Benchmark Studies
This report uses a two-step probabilistic structural health monitoring approach to analyze the Phase II simulated and experimental benchmark studies sponsored by the IASC-ASCE Task Group on Structural Health Monitoring. The studies involve damage detection and assessment of the test structure using simulated ambient-vibration data and experimental data generated by various excitations. The two-step approach involves modal identification followed by damage assessment using the pre- and post-damage modal parameters based on the Bayesian updating methodology. An Expectation-Maximization algorithm is proposed to find the most probable values of the parameters. The results of the analysis show that the probabilistic approach is able to detect and assess most damage locations involving stiffness losses of braces in the braced frame cases, while the success of the approach in detecting rotational stiffness losses of the beam-column connections in the untraced cases may rely on sufficient prior information for the column stiffness
A new modal-based damage location indicator
Vibration-based damage detection techniques use the change in modal data as an indicator to assess damages in the structure. Knowing the structural dynamic characteristics of the healthy and damaged structure, the estimation of the damage location and severity is possible by solving an inverse problem. This paper presents a mathematical expression relating damage location and depth to the frequency shifts of the bending vibration modes. This expression permits the extraction of a series of coefficients that characterize each damage location and are independent of the damage severity. The vector aggregating these coefficients for a given location constitutes a Damage Location Indicator (DLI) that unambiguously characterizes the position of a geometrical discontinuity in the beam. A set of vectors typifying all locations along the beam may be used as patters opposable to the damage signature found by measurements. The similarity between the signature and one of the patterns indicates the location of damage
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