[The orthogonal polynomial regression method of multi-wavelength radiation thermometry].

For the problem of multi-wavelength radiation thermometry, the traditional data processing methods are the least squares techniques, the multiple linear regression fitting, and the stepwise regression fitting. There are some shortages in these methods, resulting in a certain error between the fitting result and the true temperature of the object surface. A new data processing method of multi-wavelength radiation thermometry--the orthogonal polynomial regression method was brought forward in this article on the base of variable emissivity. The mathematic principle of orthogonal polynomial regression method was expounded and according to the surface emissivities of tungsten, the true temperature of tungsten surface was simulated by the stepwise regression method and the orthogonal polynomial regression method. By comparing the fitting results, the authors found that the orthogonal polynomial regression method has the merit of simple principle and small operation, and the relative error between the fitting result and the surface true temperature is smaller. So the authors can draw the conclusion that using the orthogonal polynomial regression method to process the data of the multi-wavelength radiation thermometry, the fitting result has smaller error, it can fit the true temperature of object faster, and the result is more accurate than the traditional data processing methods.