基于GA-BPSO算法的艉部结构模态测点优化布置
Optimization Sensor Placement for Stern Structure Modal Analysis Based on GA-BPSO Algorithm
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摘要: [目的]针对水下航行器艉部结构振型复杂、模态测试测点多问题，本文提出了一种基于遗传算法和二进制离散粒子群混合算法（GA-BPSO）的测点优化布置方法。[方法]首先建立典型艉部结构有限元模型并提取结构参数，构建三维消冗指标和模态置信准则的组合目标函数，然后基于GA-BPSO算法对艉部结构进行模态测点优化布置。为验证优化方法的有效性，开展了艉部结构测点均匀布置和优化布置的模态实验。[结果]结果表明：优化后测点数量由均匀布置方案的840个减少至200个，优化布置方案模态置信矩阵最大非对角元素降低至0.0333，频率误差控制在1%以内，且振型吻合度较高。[结论]本文方法有效兼顾了模态振型的线性独立性和可视化效果，可用于水下艉部结构模态测试。
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关键词:
- 艉部结构 /
- 测点优化布置 /
- 遗传算法（GA） /
- 二进制离散粒子群算法（BPSO） /
- 三维消冗组合目标函数
Abstract: [Objectives] Aiming at the problem of complex vibration modes and multiple modal test points of the stern structure of underwater vehicles, a sensor optimization layout method based on genetic algorithm and binary discrete particle swarm hybrid algorithm (GA-BPSO) is proposed in this paper. [Methods] Firstly, a finite element model of a typical stern structure is established and structural parameters are extracted, and a combined objective function of three-dimensional redundancy elimination index and modal confidence criterion is constructed. Then, the modal measurement points of the stern structure are optimally arranged based on the GA-BPSO algorithm. To verify the effectiveness of the optimization method, modal experiments with uniform and optimal arrangement of measurement points of the stern structure are carried out. [Results] The results show that, the optimized placement reduces the number of test points from 840 to 200. The maximum off-diagonal element in the modal confidence matrix of the optimized placement is reduced to 0.0333, with frequency errors controlled within 1% and high modal shape correlation. [Conclusions] The proposed method effectively balances the linear independence of modal shapes and the visualization quality, making it suitable for modal testing of underwater stern structure. -
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