基于改进DPSO算法的航空发动机失谐叶片排序

通过叶片模态实验获得叶片失谐参数，建立了叶盘系统动力学模型，提出了一种新的排序方式.在标准粒子群算法中引入遗传算法的交叉算子和变异算子以及遗传选择的思想，利用罚函数法兼顾错频与减振的应用需求，保留了粒子群算法收敛较快的优秀特性，改善了粒子群的全局寻优能力，并得到比其他优化算法精度更高的排序结果.结果表明，恰当的叶片排布顺序可有效降低叶盘系统振动局部化，采用提出的离散遗传粒子群算法进行叶片排布可使叶盘系统振动幅度较小或者在可接受范围内.

Mistuned Blade Sorting Based on Improved DPSO Algorithm for Aero-Engine

A dynamic model of bladed-disk system was established with mistuning parameters obtained by the modal experiment, and a new sorting method was proposed. The crossover operator, mutation operator and genetic selection of the genetic algorithm were introduced into the standard particle swarm algorithm and the penalty function was taken to balance the application requirements of the mistuning and vibration reduction. In this way the excellent characteristic of faster convergence of the particle swarm algorithm was retained, the particle swarm global optimizing ability was improved, and the ranking result accuracy was higher than that of other optimization algorithms. The results showed that appropriate blade arrangement sequence could effectively reduce the vibration localization of the bladed-disk system, and the proposed discrete genetic particle swarm algorithm could make vibration amplitude smaller or within the acceptable range of the bladed-disk system.