Abstract
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.
Highlights
The first documentation of fatigue failure in metals is often credited to Wilhelm Albert who, in 1838, reported failures due to small repeated loads substantially less than the ultimate tensile strength of the components [1]
Individual thermoelastic stress analysis (TSA) data fields are shown at selected cycle numbers, illustrating that changes in the measured optical flow crack length, crack length based on phase information, and the Euclidean distance between feature vectors representing the initial and current state, correspond to qualitative changes in the data fields
The Euclidean distance calculated using both the whole field of view and the defined region of interest (ROI) is approximately zero from 98 000 to 120 000 cycles, i.e. there is no significant change in the shape of the TSA data fields (S in equation (2.1)) and, there is no damage in the specimen sufficient to change the strain field
Summary
The first documentation of fatigue failure in metals is often credited to Wilhelm Albert who, in 1838, reported failures due to small repeated loads substantially less than the ultimate tensile strength of the components [1]. In safety critical structures such as airframes, the early detection of damage, and higher resolution information on the behaviour of that damage, would allow earlier or more targeted remedial measures to be undertaken. Measurements are usually made of the amplitude of temperature resulting from cyclic loading that induces elastic strains and stresses under adiabatic conditions, i.e. at a sufficiently high frequency that there is no significant heat transfer. In these circumstances, the temperature change, ΔT is given by [8]: DT
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