基于灵敏度分析的纺纱过程多相关参数质量优化策略

IF 2.3 4区 工程技术 Q2 ENGINEERING, MECHANICAL
Sheng Hu, Di Wu, Xi Zhang, Pinjian Wang
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引用次数: 0

摘要

针对纺纱过程中多相关参数的质量优化问题,本文提出了一种基于麻雀搜索算法(SSA)的新方法。首先,利用广义回归神经网络(GRNN)研究纺纱工艺参数对纱线质量的影响,建立纺纱工艺质量前向模型。并根据纺纱工艺参数的耦合性和相关性特点,采用灵敏度分析法分析各纺纱工艺参数对纱线质量的影响,对相关纺纱工艺参数作进一步分析。然后建立了带纺纱工艺参数的质量优化模型,并利用 SSA 对纺纱工艺中多相关参数的质量优化模型进行求解。最后,通过实例验证了所提方法的有效性。结果表明,最优纺纱工艺参数组合生成[32.159 5.2 0.8 14.8 24.540 8588.677 21.708]的配置,适配值为 0.0003。所提出的基于灵敏度分析的质量优化策略在收敛速度和优化精度方面都有很好的表现,这将为提高纱线质量提供指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sensitivity analysis-based quality optimization strategy for multi-correlation parameters in spinning process
To address the problem of quality optimization of multi-correlation parameters in the spinning process, this paper proposes a new method based on a sparrow search algorithm (SSA). Firstly, a generalized regression neural network (GRNN) is used to investigate the impact of the spinning process parameters on yarn quality, and quality forward modeling in the spinning process is established. And based on the coupling and correlation characteristics of spinning process parameters, sensitivity analysis is used to analyze the influence of each spinning process parameter on yarn quality, the correlation spinning process parameters for further analysis. Then a model of quality optimization with spinning process parameters is established, and SSA is used to solve the model of quality optimization with multi-correlation parameters in the spinning process. Finally, the effectiveness of the proposed method was validated through an instance. The results show that the optimal spinning process parameters combination generation of [32.159 5.2 0.8 14.8 24.540 8588.677 21.708] occurs in a configuration with a fitness value of 0.0003. The proposed sensitivity analysis-based quality optimization strategy reveals good performances in terms of both convergence speed and optimization accuracy, which will provide guidance for improving yarn quality.
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来源期刊
CiteScore
3.80
自引率
16.70%
发文量
370
审稿时长
6 months
期刊介绍: The Journal of Process Mechanical Engineering publishes high-quality, peer-reviewed papers covering a broad area of mechanical engineering activities associated with the design and operation of process equipment.
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