Intelligent optimization algorithm for turbine blade assembly
Turbine component assembly is an important component of the engine manufacturing process.In order to ensure that the rotor imbalance after turbine blade assembly meets the design standards,it is necessary to group and test assemble the blades,which affects the efficiency of assembly.To solve this problem,a blade assembly sequence optimization method based on improved Simulated annealing algorithm is proposed.A mathematical model is established that combines the imbalance of the disc itself with the imbalance of the blades.The algorithm is improved by using multi neighborhood search mechanism,improving annealing mechanism,adding heating and memory modules.The effectiveness of the algorithm is verified through examples,and compared with butterfly algorithm,skyhawk algorithm,and original Simulated annealing algorithm,which effectively reduces the unbalance of the turbine rotor.The results show that the improved Simulated annealing algorithm can effectively reduce the imbalance after blade assembly.In order to make the algorithm more convenient to serve the assembly site,a blade assembly software was developed based on the MFC framework,providing an effective solution to solve the problems of multiple disassembly and assembly efficiency in blade assembly.
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