Attenuation of ultrasonic Lamb waves with applications to material characterization and condition monitoring.

摘要

Engineering industries usually require nondestructive evaluation (NDE) methods to ensure quality control, safety, and optimized use of resources. Among potential NDE techniques, ultrasonic wave methods are widely used because of their versatility and affordability. For applications to layered structures, ultrasonic guided waves are naturally excited and detected, so these guided waves are the preferred choice when compared to conventional bulk waves. The main advantage of guided waves over bulk waves for layered structures is that these guided waves can propagate a much farther distance, and thus they enable long range inspection. It is important to note that guided waves are multi-mode, so a preferred mode can be selectively used, although it is sometimes more efficient to use multiple wave modes. The characteristics of guided waves, namely dispersive propagation and attenuation, are directly related to the properties of the system in which they are propagating, so the measurement of these wave characteristics can be used for material characterization and condition monitoring.; Despite a number of successful techniques to experimentally measure propagation characteristics of guided waves, there is a lack of a standard procedure to obtain attenuation characteristics. This research develops such a quantitative and systematic procedure to extract attenuation characteristics from real guided wave time-domain signals. This research considers multiple wave-modes, and focuses on broadband attenuation measurements with laser ultrasonic techniques. The analytical model of guided waves with attenuation is studied in general cases, and a numerical simulation is developed to model the point source/receiver laser measurement system. The attenuation extraction technique is developed using synthetic signals generated by the simulation. Finally, this research demonstrates the use of experimentally-measured attenuation data for material characterization and condition monitoring by developing an inversion scheme to back-calculate material properties for a number of practical cases.