Abstract
This paper studies the use of finite element method (FEM) and decentralized fuzzy inference method (DFIM) to realize the identification problem of heat flux density of two-dimensional steady convection heat system. Establishing a set of fuzzy inference unit, according to the measured values of the temperature deviation and the calculated values of the dispersion of fuzzy reasoning, a set of fuzzy inference components is obtained. Finally, through a comprehensive weighted fuzzy reasoning component, the compensation amount of heat flux density can be received. Through numerical experiments, the effects of initial guess value, temperature measuring points and measurement errors on the results are discussed, and the results of conjugate gradient method (CGM) are compared. The results show that compared with CGM, DFIM reduces the inversion results of measurement points and the number of initial guess value depending on measurement error, and enhances the anti-interference ability, which has better anti-ill ability.
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