Monte-Carlo modelling to determine optimum filter choices for sub-microsecond optical pyrometry

When designing a spectral-band pyrometer for use at high time resolutions (sub-μs), there is ambiguity regarding the optimum characteristics for a spectral filter(s). In particular, while prior work has discussed uncertainties in spectral-band pyrometry, there has been little discussion of the effects of noise which is an important consideration in time-resolved, high speed experiments. Using a Monte-Carlo process to simulate the effects of noise, a model of collection from a black body has been developed to give insights into the optimum choices for centre wavelength and passband width. The model was validated and then used to explore the effects of centre wavelength and passband width on measurement uncertainty. This reveals a transition centre wavelength below which uncertainties in calculated temperature are high. To further investigate system performance, simultaneous variation of the centre wavelength and bandpass width of a filter is investigated. Using data reduction, the effects of temperature and noise levels are illustrated and an empirical approximation is determined. The results presented show that filter choice can significantly affect instrument performance and, while best practice requires detailed modelling to achieve optimal performance, the expression presented can be used to aid filter selection.