Multispectral radiometric temperature measurement algorithm for turbine blades based on moving narrow-band spectral windows

Abstract

This paper addresses the problem of inaccurate emissivity presets for multispectral temperature measurements of aero-engine turbine blades and proposes a narrow-band spectral window moving temperature inversion algorithm that does not rely on an assumed emissivity model. As the emissivity of the measured object changes slowly over the narrow spectral window, the temperature corresponding to the normalized spectral radiation intensity for each window in the set temperature range is calculated using the Mahalanobis distance coefficient. The temperature error is less than 1.33% relative to thermocouple measurements when using this algorithm to perform temperature inversion on the experimental spectrum curves for different types of alloy samples. Furthermore, a two-dimensional spectral temperature field measurement platform was built, and the surface temperature fields of alloy samples were reconstructed using the narrow-band spectral window moving algorithm. The proposed algorithm is shown to provide high-precision inversion of the temperature field without presetting the emissivity model, which gives a new processing concept for the application of infrared spectral temperature measurements.