In this paper, we present our progress on developing Sonic Infrared (IR) Imaging for structural health monitoring on
steel structures. Sonic IR imaging is a fast, wide-area novel imaging NDE/SHM technique. Ultrasonic excitation was
used to stimulate heating in defects, combining with Infrared Imaging to identify defects in structures. The whole
process takes only about a second. We have been working on some steel specimens used in some typical steel
structures. Actual heating patterns are extracted from the IR images and the actual temperature changes are mapped out.
Theoretical computing is also carried out to calculate the heating pattern in the specimens with the experimental results
as benchmarks.
Sensing technology and sensor development have received increased attention in the recent years, and a number of types
of sensors have been developed for various applications for materials and structures. In this paper, we will discuss the
concept of combining sensing of global vibration and local infrared imaging techniques. The global vibration-based
techniques determine the health condition of structures by the changes in their dynamic properties or responses to
external disturbs or excitations. Infrared Imaging is introduced here to detect local defects or problems so that to provide
more direct and accurate assessment about the severity and extent of the damage. The progress on developing a hybrid
structural health monitoring system is presented through the results on both the global sensing algorithm study and local
infrared imaging investigation on a steel C channel.
Sonic IR Imaging is a novel NDE technique, which combines a short ultrasonic pulse excitation and infrared imaging to detect defects in materials and structures. The ultrasound pulse, typically a fraction of a second long, causes heating in the defects, which results in the change of IR radiation from the target. This change can be detected by infrared sensors, and thus, defects can be identified. One key objective in developing this technology is to maximize the IR signal so that the probability of detection (POD) of defects is optimized. From our work, we learned that the ultrasonic frequency, coupling medium between the ultrasonic transducer and the target, the pressure from the transducer on the target, the characteristics of the target itself, etc. are all factors that affect the IR signals. In addition, different IR sensors have different responses for the same IR radiation. To develop Sonic IR Imaging technology, it is important to study the relationship between the IR signal and the input acoustic energy for different system configurations. In this paper, we'll describe the thermal energy computing tools developed for analyzing data from different sets of parameters in Sonic IR Imaging.
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