Identification of flow rate and temperature in the pipeline based on equal variance fitting of surface temperature measurement

Identification of flow rate and temperature in a heat supply pipeline based on surface temperature measurement is still at the initial stage in the field of infrared nondestructive testing, which is the key theory for the development of infrared nondestructive testing. In order to solve the problem that the flow rate identification result was less accurate than the temperature identification result and the accuracy of the identification method based on least square fitting was limited, a heat transfer model of the fully developed region of the pipeline had been built based on Gnielinski correlation equation, and the identification problem had been solved by Levenberg-Marquardt(L-M) algorithm based on surface temperature measurement. Through theoretical derivation and numerical examples, it has been found that the parameter relative identification error is inversely proportional to the absolute value of the product of the sensitivity maximum and the true value of the parameter, and the variance between the measurement temperature distribution with measurement error and the temperature distribution based on least square fitting is not equal to the product of the standard deviation of the measurement error and the number of measurement points. The identification method based on equal variance fitting of surface temperature measurement was proposed. Numerical experiments have proved that the method can accurately identify the flow rate and temperature in the pipeline with measurement error.