对旋风机双排叶片耦合多目标优化及特性分析

    Multi-objective optimization and characteristic analysis of contra-rotating fan double-row blades coupling

    • 摘要: 为提高矿用对旋风机气动性能,保障井下安全工作环境,基于前馈神经网络代理模型和遗传算法进行对旋风机双排对旋叶片耦合多目标优化。首先,参数化建模对旋风机2级叶片,选取各叶高截面安装角和中弧线控制参数作为高维优化变量;其次,在高维决策空间进行拉丁超立方采样得到决策样本集,通过数值仿真求解决策样本集对应的气动样本集;运用样本集数据构建神经网络代理模型,结合遗传算法优化神经网络的权值和阈值,提高代理模型的泛化能力;以小流量、设计流量、大流量工况下对旋风机整机全压效率最大为优化目标,采用遗传算法全局寻优输出帕累托解集,确定全工况对旋风机整机全压效率提升最大的几何参数组合,得到优化后对旋风机模型;运用数值仿真验证优化结果,对比分析优化前后对旋风机气动性能和流场分布情况。结果表明:对旋风机在小流量、设计流量、大流量工况下整机全压效率分别提高了0.59%、0.88%、1.21%,稳定运行工况范围明显拓宽;优化后第1级叶片安装角的增大在提高流动稳定性的同时带来部分能量损失,第2级叶片安装角减小,叶片做功能力增大,叶轮气动效率提高;优化后2级叶片叶顶附近高熵区范围和熵值减小,流动分离和尾迹损失现象减弱,叶顶截面相对速度分布改善,对旋风机对流量变化的适应性增强。

       

      Abstract: To enhance the aerodynamic performance of contra-rotating fan and ensure the safe working environment of mine, based on feedforward neural network agent model and genetic algorithm, the multi-objective optimization of contra-rotating fan double-row blades coupling is carried out. Initially, double-row blades of the contra-rotating fan are parameterized, with the installation angles of each blade’s height span and the control parameters of the mean cambers selected as high-dimensional optimization variables. Secondly, Latin hypercube sampling is conducted in the high-dimensional decision space to obtain the decision sample set, and the aerodynamic sample set corresponding to the decision sample set is solved through numerical simulation. The sample set data is used to construct a neural network surrogate model, and the weights and thresholds of the neural network are optimized in combination with the genetic algorithm to improve the generalization ability of the surrogate model. The optimization objectives focus on maximizing total pressure efficiency of contra-rotating fan at low, design and high flow rates, with genetic algorithm used for global optimization to output the Pareto optimal solution set, the optimal geometric parameter combinations that maximize total pressure efficiency across all operating conditions are then determined, leading to the optimized contra-rotating fan model; the optimization results are verified by numerical simulation, and the aerodynamic performance and flow field distribution of the contra-rotating fan before and after optimization are compared. The results indicate that the overall pressure efficiency of contra-rotating fan has improved by 0.59%, 0.88% and 1.21% under low, design and high mass flow rates, respectively, significantly broadening the range of stable operating conditions; after optimization, the increase of the first-stage blade installation angle can improve the flow stability while causing partial energy loss, and the decrease of the second-stage blade installation angle can increase the blade’s work ability and improve the impeller’s aerodynamic efficiency; the range and entropy of the high entropy area near the tip of the two-stage blade are reduced, the flow separation and wake loss are weakened, the relative velocity distribution of the tip section is improved, and the adaptability of contra-rotating fan to the change of mass flow rate is enhanced.

       

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