基于PI定理的船舶冲击环境预报方法研究

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摘要考虑到船舶水下非接触爆炸冲击响应的强非线性传递规律，采用聚类以及二分聚类算法搭建的RBF网络对其冲击响应的谱速度值加以训练和预报。在网络中，选取仿真计算过程中涉及到的诸多参变量来表征船舶冲击环境的特征参数，利用量纲分析及π-定理理论分析方法将原始特征参数转换为无量纲量并且剔除不适应的参量。结果表明参数无量纲化处理可以提高网络对响应谱速度值的预报准确性，并使预报值偏离仿真结果10%范围内的占比有明显提升，此外得出结合无量纲参数的二分聚类RBF网络模型对冲击环境谱速度值的预报效果最佳。

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	赵晓俊1
	郭君1
	杨俊杰2
	王茀凡1

关键词 ：冲击响应, 无量纲, 神经网络, 聚类

Abstract：Considered many non-linear transmission relationships of underwater non-contact explosion response of ships, a method of RBF network built by K-means clustering and binary K clustering algorithm was applied to train and forecast the velocity spectrum of the impact response. In this network, many variables involved in the simulation are available to represent the characteristic parameters, and the dimensional analysis and π-theorem theory analysis are used to convert the characteristic parameters into dimensionless ones and eliminate the unsuitable parameters. The experimental results show that the dimensionless processing of parameters can improve the accuracy of the network's prediction of velocity spectrum, and significantly increase the proportion of the prediction value deviating from the simulation result within the range of 10%. In addition, it is concluded that the binary K clustering RBF network model combining with the dimensionless parameters has the best prediction effect on the impact spectrum value.

Key words： impact response dimensionless neural network clustering analysis

收稿日期: 2022-07-23 出版日期: 2023-10-15

引用本文:

赵晓俊1，郭君1，杨俊杰2，王茀凡1. 基于PI定理的船舶冲击环境预报方法研究[J]. 振动与冲击, 2023, 42(19): 137-143.
ZHAO Xiaojun1, GUO Jun1, YANG Junjie2, WANG Fufan1. A method for predicting ship impact environment based on PI theorem. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(19): 137-143.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2023/V42/I19/137

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