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A method for ranking turbine rotor blades based on Monte Carlo tree search

A sorting method and a technology of moving blades, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as poor optimization effect and difficulty in determining heuristic functions, achieve increased breadth, break through the lower limit of optimization, and optimize significant effect

Active Publication Date: 2019-01-11
XI AN JIAOTONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the genetic algorithm still has room for improvement in optimizing the leaf sorting problem. In order to find a better solution, various genetic operators need to be carefully designed
When the ant colony algorithm deals with the leaf sorting problem, because the heuristic function is difficult to determine, the optimization effect in dealing with the leaf sorting problem is poor

Method used

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  • A method for ranking turbine rotor blades based on Monte Carlo tree search
  • A method for ranking turbine rotor blades based on Monte Carlo tree search
  • A method for ranking turbine rotor blades based on Monte Carlo tree search

Examples

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Effect test

Embodiment 1

[0096] According to the method of the present invention, taking the blade data provided by the document "Jia Jinxin, Li Quantong, Gao Xingwei, Chen Wei, "Application of Genetic Algorithm in Optimal Ranking of Blade Mass Moment", "Journal of Aerodynamics", 2011-01 as an example, this The optimal unbalance amount finally obtained by the method of the invention is 0.00927 g·mm, and the optimization effect is remarkable compared with the result of 0.4709 g·mm in the literature. The specific order is as follows:

[0097] Table 1 Leaf sorting sequence calculated by the present invention

[0098]

[0099]

Embodiment 2

[0101] According to the method of the present invention, taking the sorting of a certain 78 moving blades as an example, this example has more blades and a larger scale than the problem in the first embodiment. The ant colony algorithm, the genetic algorithm and the method of the present invention are used to compare the optimization results, and 20 optimizations are set, and each optimization iteration is 100 times.

[0102] like image 3 As shown, all three methods can converge to a better solution in fewer iterations.

[0103] like Figure 4 As shown in (a), comparing the time consumption of each optimization process, the present invention slightly increases the time consumption of the optimization process compared with the other two algorithms, but the distribution difference of the optimal solution is small, and the optimal solution is better than the other two algorithms. .

[0104] Consider the larger initial unbalance, that is, the effect of the sealing blade, such ...

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Abstract

The invention discloses a method for ranking turbine rotor blades based on Monte Carlo tree search method for ranking turbine rotor blades based on Monte Carlo tree search, belonging to the mechanicalassembly field. Firstly, the leaf parameters are extracted. Then, the root node of Monte Carlo tree is initialized, and different leaf sequences are generated by selecting nodes, expanding nodes andsimulating nodes for many times, and the unbalance quantity is calculated, and the weight value in Monte Carlo tree is updated. Secondly, the node with the largest weight and the corresponding optimalsequence are taken as output, the root node of the Monte Carlo tree is updated again, a new Monte Carlo tree is created, and the above process is repeated. Finally, the optimal unbalance quantity andits corresponding blade sequence are obtained by searching multiple Monte Carlo trees, and the rotor blade scheduling is optimized. The invention can further optimize the blade scheduling problem while ensuring good convergence, and the algorithm has good stability.

Description

technical field [0001] The invention belongs to the technical field of mechanical assembly, and in particular relates to a method for sorting turbine rotor blades based on Monte Carlo tree search. Background technique [0002] Due to the influence of blade machining error, material unevenness, sealing blade and other factors, the weight of the turbine moving blade will be different, resulting in a residual unbalance after the entire rotation of the moving blade is installed. The turbine rotor is usually in a state of high-speed rotation, and the residual unbalance of the rotor blade stage easily causes the vibration of the rotor, and even induces the instability of the rotor under certain conditions, which affects the safe operation of the unit. Numerical analysis can prove that installing moving blades in random arrangement is easy to produce a great unbalance. Therefore, in order to improve the safety performance of the unit and reduce the unbalance caused by the installat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
CPCG06F30/20G06F2111/10
Inventor 张荻王崇宇刘天源谢永慧
Owner XI AN JIAOTONG UNIV
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