Publication | Open Access
Non-classical nonlinear feature extraction from standard resonance vibration data for damage detection
40
Citations
14
References
2014
Year
EngineeringMechanical EngineeringFeature ExtractionStructural EngineeringStructural IdentificationGeotechnical EngineeringDamage MechanismData SciencePattern RecognitionDamage DetectionInternal DamageStructural DynamicStructural VibrationEarthquake EngineeringConcrete TechnologyStructural Health MonitoringImproved Damage DiagnosticsCement-based Construction MaterialCivil EngineeringInternal Damage LevelsRandom VibrationStructural MechanicsDamage Evolution
Dynamic non-classical nonlinear analyses show promise for improved damage diagnostics in materials that exhibit such structure at the mesoscale, such as concrete. In this study, nonlinear non-classical dynamic material behavior from standard vibration test data, using pristine and frost damaged cement mortar bar samples, is extracted and quantified. The procedure is robust and easy to apply. The results demonstrate that the extracted nonlinear non-classical parameters show expected sensitivity to internal damage and are more sensitive to changes owing to internal damage levels than standard linear vibration parameters.
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