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RESEARCH ON DATA PROCESSING METHOD OF MULTI-SPECTRAL THERMOMETER Good morning everyone, Im Zhang Mingyao. I feel very honored to have a speech here. The topic of my speech today is research on data processing method of multi-spectral thermometry for the measurement. OK, Now we get down to business. To improve the measuring precision of true temperature and spectral emissivity, the dissertation brings forth the new ideas and work as follows: (1) A brightness temperature approach is proposed and used for the measurement of the true temperature and spectral emissivity. (2) A continuous measurement method based on brightness temperature is proposed by processing the measured data of the multiwavelength pyrometer at two different times, the true temperatures and spectral emissivities at two different times can be calculated simultaneously. (3) The effects of the random noise on the measured results, which are based on brightness temperature approach method and continuous measurement method, are evaluated. (4) The feasibility of applying of brightness temperature approach method and continuous measurement method in practical application are verified. Below, the emissivity model selection: efficient wavelength by eight wavelength radiation thermometer are respectively 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.1 μ m, temperature range of simulation for 1500~3000K, the temperature interval is 50K. At each temperature point used as shown in Figure 1 A~E five emission rate model, each class into 31 groups. Fig. 1 emission rate model This is the result of simulation error: From the table we can see, at high temperature: 1) rightness temperature approach method without noise in each channel, for the same emission rate model, the absolute error of the calculation of the true temperature increases with increasing temperature. 2) For A model, compared with the processing method of data based on BP network, brightness temperature approach method results in higher accuracy.