Generalized inverse matrix normalization algorithm to extract high-temperature data from multiwavelength pyrometry

doi:10.1063/5.0016747

Generalized inverse matrix normalization algorithm to extract high-temperature data from multiwavelength pyrometry

2020-10-15

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DOI：10.1063/5.0016747

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Multiwavelength pyrometry (MWP) is one of the most powerful tools for the precise measurement of high temperatures on the surfaces of non-gray materials. However, the unknown spectral emissivity of target materials is the most difficult obstacle to overcome in processing temperature inversion data using MWP. A direct and fast generalized inverse matrix normalization (GIM-NOR) data processing algorithm based on GIM theory for underdetermined equations is proposed in order to minimize the effects arising from unknown emissivity. The shape of the emissivity distribution is obtained so that the channel with the greatest emissivity can be selected in order to obtain a value close to the real temperature. The final inversion accuracy is then further improved using a NOR compensation method. Six kinds of materials with a distribution of emissivities at 1800 K were used to simulate and verify the proposed algorithm. The results show that the average relative error of temperature inversion was 0.63%, obtained within 8 ms computation time using a standard desktop computer, and the accuracy and efficiency were largely unaffected when 5% random noise was inserted into the simulation data. A set of experimental data for rocket nozzle temperature measurements with MWP were also processed based on the proposed novel algorithm. The results show that the relative error on the temperature was less than 0.50%, for a design temperature of 2490 K, and that the processing efficiency was very high, that is, within 9 ms. Simulation and experiment both proved that the proposed efficient data processing algorithm for MWP based on GIM theory was unaffected by emissivity and achieved good inversion precision and fast data processing. Therefore, the proposed new data processing algorithm for MWP data for measuring transient high temperatures has very broad potential applications, and it also provides a theoretical basis for measuring high-temperature fields using MWP.

Generalized inverse matrix normalization algorithm to extract high-temperature data from multiwavelength pyrometry

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