| About this Abstract |
| Meeting |
MS&T21: Materials Science & Technology
|
| Symposium
|
Advances in Metallic Coated Advanced Steels
|
| Presentation Title |
Optimal Wavelength Selection for Improved Multi-wavelength Pyrometry of Advanced High Strength Steel |
| Author(s) |
Fatima K. Suleiman, Kaihsiang Lin, Kyle J. Daun |
| On-Site Speaker (Planned) |
Fatima K. Suleiman |
| Abstract Scope |
Accurate pyrometry during thermal processing of advanced high strength steels (AHSS) requires detailed knowledge of the spectral emittance of the steel, which varies with the as-received state of the coil and evolves during annealing due to oxidation. Multi-wavelength pyrometers, which use irradiance measurements at an increased number of detection wavelengths, have proven effective at capturing some of these complex wavelength-dependent variations in emissivity. However, multi-wavelength pyrometry estimates are also prone to over-fitting due to their increased degrees of freedom, which may lead to large errors in the inferred temperature. This study employs the Bayesian methodology to determine the optimal combination of detection wavelengths that minimizes the posterior covariance on the temperature estimates. Using in-situ measurements from annealed DP980 coupons, the expected temperature variance is compared for various wavelength combinations in the near-infrared range. This paper presents a generalized framework for optimizing multi-wavelength pyrometers for accurate temperature estimates on high-performance steels. |