Transient distribution thermal load alternating direction weighted fuzzy inversion method

Abstract

The invention relates to the technical field of heat transfer theory inversion, in particular to a transient distribution heat load alternating direction weighted fuzzy inversion method. Comprising the following steps: step 1, establishing a heat transfer model of a measured object, arranging Nm temperature measurement points on a measured surface, initializing a transient distribution thermal load detection problem, and setting an initial value n = 0 of an inversion process iteration number identification in an initial guess value matrix of a given boundary thermal load; and 2, solving a heat transfer positive problem according to the guess value, obtaining a temperature calculation value matrix at the measuring point, calculating a temperature error matrix, judging whether En meets an iteration stopping condition or not, stopping iteration if the En meets the iteration stopping condition, and outputting the distributed heat load. According to the method, the requirement for the number of measuring points is obviously reduced, the method is not sensitive to the initial guess value of the boundary thermal load, and the method has good anti-interference capacity for measuring errors.

Description

technical field [0001] The invention relates to the technical field of heat transfer inversion, in particular to a weighted fuzzy inversion method for alternating directions of transient distributed heat loads. Background technique [0002] Inverse Heat Transfer Problem (IHTP) refers to the inverse of some unknown characteristic parameters of the system, such as boundary conditions, thermophysical parameters, geometry, initial conditions and source items, etc. The inverse heat transfer problem has a wide range of applications in aerospace, power engineering, material processing, bioengineering and non-destructive testing. [0003] The inverse heat transfer problem is usually an ill-posed (Ill-Posed) problem in the Hadamard sense, that is, the existence, uniqueness and stability of the solution cannot be satisfied simultaneously. Due to the ill-posed nature of the inverse problem, for classical inversion algorithms such as Conjugate Gradient Method (CGM) and Levenberg-Marqu...

AI Technical Summary

Problems solved by technology

Although the decentralized fuzzy inference method has been studied in the heat transfer inverse problem, however, this method has not been effectively applied to solve the unsteady state heat transfer inverse problem

The difficulty of applying the decentralized fuzzy inference method to solve the unsteady inverse heat transfer problem lies in the construction of an appropriate comprehensive weighting method for the unsteady inverse problem. An inappropriate weighting method will not only seriously affect the convergence speed, but even cause the inversion results to diverge.

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