| Inverse heat transfer problems (IHTP ) is a typical inverse subject, which involves the determination of thermophysical properties, geometric parameters, boundary conditions and source heat based on the internal or surface temperature of the object studied. IHTP is widely used in scientific research and the engineering filed such as aerospace, chemicals, materials processing, power engineering, metallurgical engineering, nondestructive testing, etc. It is of significant scientific and engineering value to further study the IHCP.Fuzzy inference is a typical uncertain reasoning method and calculation framework on the basis of the fuzzy set theory. It has the low computational cost and the strong capacity of resisting disturbance to input information and can effectively use the imprecise and incomplete information for reasoning and decision-making. What's more, qualitative knowledge (including experience knowledge) and quantitative knowledge can both be applied in fuzzy inference process. In this paper the inverse problem of steady heat transfer process is studied based on the fuzzy inference, the main works include the following five parts:①Take the problem of estimating the flat boundary temperature for example, the inverse model of heat transfer process is established on the typical optimal algorithms such as CGM, L-MM and GA. Through numerical simulation experiments, the influence of different initial guesses of the estimated parameters, the number of temperature measuring points and measurement errors on the inversion results are discussed, and the limitation of the before-mentioned method used for solving the inverse heat transfer problems are summarized.②For the limitation of the optimization algorithm used for solving the inverse heat transfer problems, a new idea based on fuzzy logical theory is presented to study the inverse heat transfer problem, and for the inherent spatial distribution characteristics among measured information and the estimated information of the inverse thermal boundary conditions problem, the decentralized fuzzy inference (DFI) strategy tending to solve the inverse heat transfer problems is proposed. And then the decentralized fuzzy inference system is set up based on DFI strategy for two-dimensional inverse steady heat transfer problem. According to the local measured information and the fuzzy inference rules, the system utilizes a set of decentralized fuzzy inference units to produce the fuzzy inference components which are corresponding to the local measured information. Further, depending on the importance of the estimated information for local measured information, the fuzzy inference components are synthesized. And under the premise of considering all the measured information, the compensations of estimated information are gained, and the estimation is achieved.③The synthetic issue on the fuzzy inference results in the DFI system is studied, and the synthesized method based on influence relation matrix for DFI system is presented. For the inverse heat transfer problem to estimate thermal boundary conditions of heat transfer system on regular domain, the influence relation matrix is gained by the qualitative analysis of the heat transfer process, by which the influence relation matrix of two typical heat transfer system on regular domain is established, and the qualitative weighting decentralized fuzzy inference (QDFI) method is formed. For some complicated inverse heat transfer problem on irregular domain, the sensitivity analysis is used to build the influence relation matrix, and the sensitivity weighting decentralized fuzzy inference (SDFI) is formed. The DFI is performed to estimate the temperature boundary of a flat and the geometry of a tube inner surface, and the results are compared with the CGM to show its validity.④The heat flux distribution at the metal-mold interface and the temperature distribution at furnace inner surface are solved by QDFI method respectively, and the influence of initial guesses of the inverse parameters, the number of measuring points and measurement errors on thermal boundary conditions results are discussed. From the results, it can be concluded that DFI compared to CGM can reduce the dependence of results on the number of measuring points and weaken the effect of measurement errors on the results. The DFI is of a good anti ill-posed characteristic for solving inverse problem of the actual distribution parameters heat transfer system.⑤The thermal boundary conditions of membrane water wall, which are comprised of the radiation heat flux at the fireside, the temperature of the working steam-water-mixtures and the convective heat transfer coefficient in the water wall tubes, are estimated in the same time by the SDFI method based on the local measured temperatures on the back of membrane water wall, and the influence of the different inverse conditions on the results are discussed. In comparison with CGM, it is concluded that SDFI is of a good anti ill-posed characteristic. The study shows that DFI can determine the thermal boundary conditions of membrane water wall, the temperature distribution of the fireside and the positions of the dangerous points more effectively based on the local measured temperatures on the back of membrane water wall. It would provide necessary basis for the operation state analysis and monitoring of power plant boilers. |
