Turbine moving blade sequencing method

Abstract

The invention relates to a turbine moving blade sequencing method. The turbine moving blade sequencing method comprises following steps: 1) carrying out grouping, taking all moving blades as originalsamples, and dividing the moving blades into several groups; 2) carrying out intra-group optimal sequencing, and carrying out optimization sequencing on samples in each group through an enumeration method; and 3) carrying out inter-group optimal sequencing, carrying out optimization sequencing on the groups through the enumeration method, and determining the final sequence of the original samples.The turbine moving blade sequencing method strives to determine the assembling sequence of the turbine moving blades under reasonable calculated quantity, and to control the amount of unbalance generated by the moving blades to a minimum level, through grouping, the intra-group blade sequence is first optimized, then the sequence of the groups is optimized again, the amount of unbalance is reduced, and therefore the finally-obtained total amount of unbalance is low, and the turbine moving blade sequencing method can also carry out blade sequencing in an occasion having a large number of blades and having an exact demand on the amount of unbalance.

Description

technical field [0001] The invention belongs to the technical field of mechanical assembly, relates to the installation of moving blades in a turbomachine, and relates to a method for sorting turbine moving blades. Background technique [0002] Due to the influence of factors such as machining errors, uneven materials, and structural differences between blades, the weight (or the weight moment relative to the rotating shaft) of each moving blade in the turbomachinery will inevitably be different. A ring of moving blades assembled in a certain order will produce an unbalanced amount. During normal operation of turbomachinery, the turbine rotor usually rotates at high speed, and the residual imbalance of the rotor can cause vibration. For the safe and stable operation of turbomachinery, it is necessary to control all kinds of original unbalance. To control the amount of unbalance produced by the moving blades, it is necessary to determine the proper assembly sequence of the ...

AI Technical Summary

Problems solved by technology

Among various optimization algorithms, the enumeration method enumerates all possibilities, and then verifies them one by one to obtain the optimal result. The optimal solution obtained is definitely the best, but it is also the lowest in efficiency; Large, the enumeration method is considered to be extremely inefficient, so it is considered that the enumeration method cannot be used, and most of them use genetic algorithms for optimization, such as 1) Dai Yiping, Jiang Caijun, Lu Shiming, "Leaf Installation Sorting Based on Genetic Algorithms" Development and Application of Optimization System" ("Steam Turbine Technology", Issue 5, 2003), 2) Tang Shaojun, Wang Xu, Zhu Bin, "Application of Genetic Algorithms to the Sorting of Compressor Blades" (Journal of Aerodynamics; Issue 03, 2005) , 3) Jia Jinxin, Li Quantong, Gao Xingwei, Chen Wei, "Application of Genetic Algorithms in Optimum Sorting of Blade Mass Moments" ("Journal of Aerodynamics", Issue 01, 2011), etc.

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