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A synthetic time-reversal imaging method for structural health monitoring
528
Citations
22
References
2004
Year
Image ReconstructionEngineeringSensor ArrayMechanical EngineeringAdvanced ImagingStructural IdentificationTime ReversalSmart StructureHealth SciencesStructural VibrationRadiologyAcoustic MicroscopyMedical ImagingStructural Health MonitoringInverse ProblemsUltrasoundArray ProcessingTime-reversal ConceptBiomedical ImagingMechanical SystemsStructural MechanicsVibration ControlStress Waves
The study investigates applying the time‑reversal concept to guided waves in plate‑like structures, where dispersive, multi‑mode stress waves are present. A digital imaging method for distributed sensor/actuator networks was developed based on the time‑reversal principle. The method achieves temporal and spatial focusing, enables efficient imaging of damage location and size, and enhances signal strength enough to reduce the number of sensors and actuators needed, though exact waveform reconstruction is limited by flexural wave dispersion.
This paper presents an experimental and theoretical investigation of the applicability of the time-reversal concept to guided waves in plate-like structures, where the stress waves are dispersive and of multi-modes. It is shown that temporal and spatial focusing can be achieved through time reversal, although the dispersive behaviour of the flexural waves renders it impossible to exactly reconstruct the waveform of the original excitation. Based on the principle of the time-reversal concept, a digital imaging method suitable for distributed sensor/actuator networks has been developed. This new method, which overcomes the limitation of the conventional phased array method that operates under pulse-echo mode, provides an efficient imaging method for locating and approximate sizing of structural damages. In addition, it has been shown that signal strengths can be considerably enhanced by applying the present synthetic time-reversal method, thus reducing the number of sensors and actuators required to achieve a given signal-to-noise ratio.
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