Optical-flow-based motion compensation algorithm in thermoelastic stress analysis using single-infrared video

<p>Thermoelastic stress analysis (TSA) is a non-contact measurement technique for stress distribution evaluation. A common issue related to this technique is the rigid-displacement of the specimen during the test phase, that can compromise the reliability of the measurement. For this purpose, several motion compensation techniques have been implemented over the years, but none of them is provided through a single measurement and a single sample surface conditioning. Due to this, a motion compensation technique based on Optical-Flow has been implemented, which greatly increases the strength and the effectiveness of the methodology through a single measurement and single specimen preparation. The proposed approach is based on measuring the displacement field of the specimen directly from the thermal video, through optical flow. This displacement field is then used to compensate for the specimen’s displacement on the infrared video, which will then be used for thermoelastic stress analysis. Firstly, the algorithm was validated by a comparison with synthetic videos, created ad hoc, and the quality of the motion compensation approach was evaluated on video acquired in the visible range. The research moved into infrared acquisitions, where the application of TSA gave reliable and accurate results. Finally, the quality of the stress map obtained was verified by comparison with a numerical model.</p>

Detection and tracking of cracks based on thermoelastic stress analysis

Thermoelastic stress analysis using arrays of small, low-cost detectors has the potential to be used in structural health monitoring. However, evaluation of the collected data is challenging using traditional methods, due to the lower resolution of these sensors, and the complex loading conditions experienced. An alternative method has been developed, using image decomposition to generate feature vectors which characterize the uncalibrated map of the magnitude of the thermoelastic effect. Thermal data have been collected using a state-of-the-art photovoltaic effect detector and lower cost, lower thermal resolution microbolometer detectors, during crack propagation induced by both constant amplitude and frequency loading, and by idealized flight cycles. The Euclidean distance calculated between the feature vectors of the initial and current state can be used to indicate the presence of damage. Cracks of the order of 1 mm in length can be detected and tracked, with an increase in the rate of change of the Euclidean distance indicating the onset of critical crack propagation. The differential feature vector method therefore represents a substantial advance in technology for monitoring the initiation and propagation of cracks in structures, both in structural testing and in-service using low-cost sensors.