Damage assessment of composite plate structures with material and measurement uncertainty

Chandrashekhar, M.; Ganguli, Ranjan

doi:10.1016/j.ymssp.2015.12.021

Cited by 51 publications

(20 citation statements)

References 29 publications

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“…To fulfill this purpose, the concept of structural health monitoring (SHM) was proposed, and there has been great development in the SHM area utilizing dynamic measurements in the last few decades 1 . A large amount of methods has been proposed in this research area and applied to various types of basic structural members, laboratory models, and even real‐life structures, including trusses, 2–4 beams and frames, 5–11 plates and shells, 12–18 periodic structures, 19–23 hydraulic steel structures, 24–26 buildings, 27–33 and bridges 34–40 . However, in addition to the specific methods employed for solving the relevant problems as mentioned above, the success of vibration‐based SHM also highly depends on the quality of collected measurement data, which is ensured by the quantity and detailed layout of employed sensors; at present, the sensor configuration is still designed based on experience in most cases by considering a series of practical constraints.…”

Section: Introductionmentioning

confidence: 99%

Optimal sensor configuration for structural response prediction by a modified Nelder–Mead simplex method

Yin

2021

Struct Control Health Monit

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Summary The optimal configuration of the sensor system is extremely critical to effectively control the test cost and ensure the quality of the collected data for structural health monitoring (SHM) system. Different from the traditional sensor configuration criterion, the information entropy measure aims to minimize the uncertainty of structural model parameters to be identified, which can ensure that the collected data provides the maximum amount of information for the model identification. However, most of the current researches within the framework of entropy measure are aimed at the model identification, while studies that consider response prediction are still rare. In this paper, by constructing the posterior predictive distribution function of the frequency response functions (FRFs) at the unmeasured positions of structures and also the corresponding information entropy representation, the optimal sensor configuration problem for the purpose of structural response prediction at the unmeasured position is studied. A modified bound‐constrained Nelder–Mead simplex method to handle the binary encoded optimization variables is also proposed, which can effectively solve the combinatorial optimization problem in the optimal sensor configuration. The methodology proposed is validated by a forced vibration study conducted for a laboratory rectangular cantilever plate. The obtained results show that the prediction error and uncertainty of the higher‐order modes of the FRFs at the unmeasured positions is generally larger than that of the lower ones. Also, by comparing the performance of worst and optimal sensor layouts, the importance of the optimal configuration for response prediction at unmeasured locations is clearly revealed especially for a small number of sensors.

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Section: Introductionmentioning

confidence: 99%

Optimal sensor configuration for structural response prediction by a modified Nelder–Mead simplex method

Yin

2021

Struct Control Health Monit

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“…Fiber reinforced plastic (FRP) composite materials are becoming increasingly popular, particularly in the aerospace field, due to their higher mechanical benefits over metals such as low weight and high stiffness and strength (Chandrashekhar and Ganguli, 2016;Baccar and Söffker, 2017;Castro et al, 2019). However, composite components can often demonstrate fragility toward low-velocity impacts (Atobe et al, 2011;Marchi et al, 2011;Ciampa et al, 2016;Ali et al, 2017), which can considerably degrade the structural integrity and, if not detected, they can result in catastrophic failures.…”

Section: Introductionmentioning

confidence: 99%

Impact Localization in Composites Using Time Reversal, Embedded PZT Transducers, and Topological Algorithms

Coles

Castro

Andreades

et al. 2020

Front. Built Environ.

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Time reversal is a powerful imaging processing technique that focuses waves at their original source using a single receiver transducer when diffusive wave field conditions are met. This has been successfully proved on various engineering components and materials using elastic waves with surface bonded transducers. This paper investigates the performance of time reversal for the localization of impact sources on fiber reinforced plastic composite structures with embedded piezoelectric sensors. A topologic approach, here named as minimum average method, is proposed to enhance the accuracy of time reversal in retrieving the impact location. Experimental tests were carried out to validate the robustness and reliability of time reversal against traditional topological approaches by altering impulsive responses contained in the baseline signals. Impact localization results revealed that time reversal and the new topological approach provided high accuracy in identifying the impact location, particularly in the presence of double impacts and material damage, which were not accounted during the initial training process. Results indicate that time reversal with embedded transducers has potential to be effective in real operating conditions, where alterations of acoustic emission responses in the baseline signals are less predictable.

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“…They developed a unified framework for the representation and quantification of uncertainty present in the fiber and matrix properties with the use of the Bayesian inference approach in order to calculate probabilistic composite fatigue failure. Chandrashekhar and Ganguli [12] performed probabilistic analysis using the Monte Carlo Simulation on a refined composite plate finite element model to calculate the statistical properties of the variation in modal parameters of a cantilever composite plate due to structural damage and material uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty of Properties and Failure Load in Composite Materials

Kędziora¹

2019

Proceedings of the 7th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

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The impreciseness (uncertainty) of the experimentally obtained data can be described using fuzzy sets theory. It is proposed the fuzzy set method for the correct and concise evaluation of various geometrical and mechanical properties or final failure load. The variability (understood as the fuzziness) of the fiber and matrix properties is described by a membership function. Based on experimental results it is possible to determine the effect of the fuzziness of the mechanical properties. The fuzzy sets theory allows to build the lower and upper bounds of the failure envelopes for the Tsai-Wu criterion. The linear qualifier function is applied to analyze the composite structure subjected to the load.

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Damage assessment of composite plate structures with material and measurement uncertainty

Cited by 51 publications

References 29 publications

Optimal sensor configuration for structural response prediction by a modified Nelder–Mead simplex method

Optimal sensor configuration for structural response prediction by a modified Nelder–Mead simplex method

Impact Localization in Composites Using Time Reversal, Embedded PZT Transducers, and Topological Algorithms

Uncertainty of Properties and Failure Load in Composite Materials

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