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

Area of Science:

• * Thermometry and optical instrumentation
• * High-speed measurement techniques

Background:

• * Spectral-band pyrometry is crucial for high time-resolution temperature measurements (sub-microsecond).
• * Optimal spectral filter characteristics for high-speed pyrometry remain ambiguous, especially concerning noise effects.
• * Previous research has not fully addressed the impact of noise on uncertainties in time-resolved pyrometry.

Purpose of the Study:

• * To investigate the impact of noise on spectral-band pyrometry performance.
• * To determine optimal center wavelength and passband width for spectral filters in high-speed applications.
• * To develop a model for understanding measurement uncertainty in time-resolved temperature measurements.

Main Methods:

• * A Monte Carlo simulation process was employed to model noise effects on black body radiation collection.
• * A validated model was used to explore the relationship between filter characteristics (center wavelength, passband width) and measurement uncertainty.
• * Data reduction techniques were applied to analyze the influence of temperature and noise levels.

Main Results:

• * A critical transition center wavelength was identified below which temperature uncertainties significantly increase.
• * Simultaneous variation of center wavelength and bandpass width impacts system performance.
• * An empirical approximation was determined to aid in filter selection, illustrating the effects of temperature and noise.

Conclusions:

• * Spectral filter selection critically influences instrument performance in high-speed pyrometry.
• * Detailed modeling is essential for optimizing spectral-band pyrometer design.
• * The derived empirical approximation offers guidance for filter selection in time-resolved measurements.