
handle: 10261/395878
A robust methodology is proposed for determining and assessing measurement uncertainties in thermal imaging systems when the Fourier coefficient-based time-reconstructed method is used. This comprehensive approach addresses factors such as camera-induced noise, setup-related errors, and data post-processing strategies. As a case study, this methodology is applied to measure a Thermal Test Chip using a thermo-reflectance setup. The results are validated with the stroboscopic boxcar averaging technique. This study yields valuable insights. The camera introduces a Rayleigh-distributed white noise, which is extracted in both post-processing methods. Image registration mitigates thermo-mechanical displacements during calibration effectively. Key uncertainties are identified for each method. Registration and calibration errors remain under 5%, with camera noise contributing only 0.5 ºC of measurement uncertainty. These uncertainties allow for accurate thermal measurements with a precision of 2 ºC and preserving a high spatial resolution (~1 μm).
Peer reviewed
Accurate thermal imaging | Cameras | Fourier Series time reconstruction | Heating systems | Imaging | Measurement uncertainty | Noise | stroboscopic boxcar averaging | Temperature measurement | Thermal management of electronics | Uncertainty, Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation, http://metadata.un.org/sdg/9
Accurate thermal imaging | Cameras | Fourier Series time reconstruction | Heating systems | Imaging | Measurement uncertainty | Noise | stroboscopic boxcar averaging | Temperature measurement | Thermal management of electronics | Uncertainty, Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation, http://metadata.un.org/sdg/9
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