| 朱全华,张涛,汪雪良,蒋镇涛,岳亚霖.结构应力逆向推演模型及其不确定度定量分析[J].装备环境工程,2023,20(3):69-76. ZHU Quan-hua,ZHANG Tao,WANG Xue-liang,JIANG Zhen-tao,YUE Ya-lin.Reverse Deduction Model of Structural Stress and Quantitative Analysis of Its Uncertainty[J].Equipment Environmental Engineering,2023,20(3):69-76. |
| 结构应力逆向推演模型及其不确定度定量分析 |
| Reverse Deduction Model of Structural Stress and Quantitative Analysis of Its Uncertainty |
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| DOI：10.7643/issn.1672-9242.2023.03.009 |
| 中文关键词: 结构安全监测 结构应力 逆向推演 数字模型 相关性分析 神经网络 不确定度中图分类号:000 文献标识码:A 文章编号:1672-9242(2023)03-0069-08 |
| 英文关键词:structural safety monitoring structural stress reverse deduction digital model correlation analysis neural network uncertainty |
| 基金项目:南方海洋科学与工程广东省实验室(广州)人才团队引进重大专项(GML2019ZD0502) |
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| Author | Institution |
| ZHU Quan-hua | Southern Marine Science and Engineering Guangdong Laboratory Guangzhou, Guangdong Guangzhou 511458, China;China Ship Scientific Research Center, Jiangsu Wuxi 214082, China |
| ZHANG Tao | Southern Marine Science and Engineering Guangdong Laboratory Guangzhou, Guangdong Guangzhou 511458, China;China Ship Scientific Research Center, Jiangsu Wuxi 214082, China |
| WANG Xue-liang | Southern Marine Science and Engineering Guangdong Laboratory Guangzhou, Guangdong Guangzhou 511458, China;China Ship Scientific Research Center, Jiangsu Wuxi 214082, China |
| JIANG Zhen-tao | Southern Marine Science and Engineering Guangdong Laboratory Guangzhou, Guangdong Guangzhou 511458, China;China Ship Scientific Research Center, Jiangsu Wuxi 214082, China |
| YUE Ya-lin | Southern Marine Science and Engineering Guangdong Laboratory Guangzhou, Guangdong Guangzhou 511458, China;China Ship Scientific Research Center, Jiangsu Wuxi 214082, China |
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| 中文摘要: |
| 目的 针对现有结构安全在线监测与评估方法存在的短板，结合人工智能方法探索新的解决方案。提出一种基于有限测点应力逆向推演整体结构应力分布的方法，以数据驱动的模式，基于神经网络技术搭建算法模型。方法 以结构有限元仿真数据为基础，运用相关性分析方法，获取代表结构响应特征的有限个测点，利用神经网络方法构建基于有限测点应力推演结构全场应力分布的算法模型。结果 以科学试验平台的连接器结构为对象，开展该算法模型的应用研究，并且对该应用实例下的算法模型开展不确定度分析，推演结果的相对不确定度u95rel为8.6%。结论 该算法模型的推演结果正确反映了结构总体响应特征。从建模过程角度分析，该算法模型的不确定度来源主要包括相关性分析方法、神经网络建模以及模型收敛条件3个方面。 |
| 英文摘要: |
| The work aims to explore an artificial intelligence method for solving the shortcomings of structural safety online monitoring and evaluation and propose a method for reversely deducing the stress distribution of the whole structure based on limited measuring points, so as to build a data-driven algorithm model based on neural network technology. Firstly, based on the finite element simulation data of the structure, a limited number of measuring points representing the structural response characteristics were obtained by the correlation analysis method. Then, neural network method was adopted to build the algorithm model of deducing stress distribution in the whole field of structure based on limited measuring points. With the connector structure of Scientific Research & Demonstration Platform (SRDP) as the object, the application of the algorithm model was studied, and the uncertainty analysis of the algorithm model in this application case was carried out. Relative uncertainty u95rel of the deduced results was 8.6%. The deduced results of this algorithm model correctly reflect the overall response characteristics of the structure. According to the modeling process, the uncertainty mainly results from correlation analysis method, neural network modeling and model convergence condition. |
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