Simultaneous Measurement of Temperature and Strain in Electronic Packages Using Multiframe Super-Resolution Infrared Thermography and Digital Image Correlation

For micro-electronic components and systems, reliability under thermomechanical stress is of critical importance. Experimental characterization of hotspots and temperature gradients, which can lead to deformation in the component, relies on accurate mapping of the surface temperature. One method of noninvasively acquiring this data is through infrared (IR) thermography. However, IR thermography is often limited by the typically low resolution of such cameras. Additionally, the unique surface finish preparations required to infer physical deformation using digital image correlation (DIC) generally interfere with the ability to measure the temperature with IR thermography, which prefers a uniform high emissivity. This work introduces a one-shot technique for the simultaneous measurement of surface temperature and deformation using multiframe super-resolution-enhanced IR imaging combined with DIC analysis. Multiframe super-resolution processing uses several subpixel shifted images, interpolating the image set to extract additional information and create a single higher-resolution image. Measurement of physical deformation is incorporated using a test sample with a black background and low-emissivity speckle features, heated in a manner that induces a nonuniform temperature field and stretched to induce physical deformation. Through processing and filtering, data from the black surface regions used for surface temperature mapping are separated from the speckle features used to track deformation with DIC. This method allows DIC to be performed on the IR images, yielding a deformation field consistent with the applied tensioning. While both the low- and super-resolution data sets can be successfully processed with DIC, super-resolution helps to reduce noise in the extracted deformation fields. As for temperature measurement, using super-resolution is shown to allow for better removal of the speckle features and reduce noise, as quantified by a lower mean deviation from the spatial moving average.