بهینه سازی عملکرد مهر انگشت بر اساس نظریه بازی فازی

Leakage and abrasion are two key performances of finger seals (FS). They not only contradict each other in FS design but also relate to many design parameters. Moreover, in the multi-objective optimization progress, the problems of optimizing results decision and preference requirement for optimization objectives are still challenge to researcher. So far, they are still important influence factors for advanced FS design. Therefore, the current work presents a new multi-objective optimization method by introducing game theory and fuzzy comprehensive evaluation theory. The optimizing results are compared to that of the general optimization method and finite element method (FEM). The study show that the FS, which is obtained by presented optimization method, has good performances. Compared respectively with the general optimization method and FEM, the computational results indicate that the presented method can effectively reflect the different response requirements of optimization objectives. Furthermore, the decision-making difficulty for multi-objective optimization of FS performances is significantly reduced.

FS is a revolutionary technology in air-to-air sealing for secondary flow control and gas path sealing in gas turbine engines. It has been demonstrated to be considerably cheaper than a brush seal but the sealing performance is similar to brush seal and better than labyrinth seal. The cost to produce FS is estimated to be 40 to 50 percent of the cost to produce brush seals [1]. Therefore it is promising in improving aero-engine performance, increasing operation life and decreasing operation cost. Research indicates that increasing stiffness can decrease the hysteresis and leakage of FS, while the contact pressure between finger feet and rotor increases synchronously and leads to the reduction of operation life for FS[2]. This contradiction is a key problem for FS application. Furthermore, the sealing performance and operation life perhaps have different response requirements in FS application. Sometimes the requirement, called “preference”, is unclear. For the FS multi-objective optimization with unclear preference, it is found that the results gained by general optimization methods are still unsatisfactory in preference and decisionmaking. Therefore, it is necessary to present an effective method to solve the above problems for FS. For the FS multi-objective optimization, the leakage (Q) and operation life (expressed by using wear ratio V generally) are taken as the two conflicting objectives. By combining fuzzy theory and the game theory, the multi-objective optimization results of different preference requirement for FS could be gained.

The current work show that FNGA method not only solved fit the FS optimization problem with different preference requirement but also reduced the optimized results decision work. Comparing with general optimization method, the FNGA method has smaller optimizing solution set. So the results decision becomes very easy and the optimizing efficiency is increased greatly.