A Probabilistic Model and Capturing Device for Remote Simultaneous Estimation of Spectral Emissivity and Temperature of Hot Emissive Materials

Estimating the temperature of hot emissive samples (e.g. liquid slag) in context harsh industrial environments such as steelmaking plants is a crucial yet challenging task, which typically addressed by means methods that require physical contact. Current remote information on emissivity sample. However, spectral dependent sample composition and itself, it hardly measurable unless under controlled laboratory procedures. In this work, we present portable device associated probabilistic model can simultaneously produce quasi real-time estimates for [0.2, 12.0 μm] range at distances up to 20 m . The robust against variable atmospheric conditions, presented together with quick calibration procedure allows field deployment rough environments, thus enabling line measurements. We validate our equipment conditions [550, 850 ° xmlns:xlink="http://www.w3.org/1999/xlink">C ] two solid well characterized emissivity's: alumina ( α- xmlns:xlink="http://www.w3.org/1999/xlink">Al 2 xmlns:xlink="http://www.w3.org/1999/xlink">O xmlns:xlink="http://www.w3.org/1999/xlink">3 ) hexagonal boron nitride xmlns:xlink="http://www.w3.org/1999/xlink">h - xmlns:xlink="http://www.w3.org/1999/xlink">BN ). analysis results yields Root Mean Squared Errors 32.3 5.7 respectively, correlated emissivity's.