摘要
焊接结构件广泛应用于航空航天、船舶制造和土木工程等领域，其疲劳寿命与可靠性直接影响系统的安全性和经济性。然而，传统疲劳寿命预测方法在复杂应力状态和多因素耦合作用下存在较大误差，难以满足工程需求。为此，本文旨在提出一种基于多源数据融合的焊接结构件疲劳寿命预测与可靠性评估方法。研究通过结合有限元分析与实验测试，建立了考虑残余应力、微观组织不均匀性和载荷谱影响的疲劳损伤模型，并引入机器学习算法优化模型参数，显著提高了预测精度。同时，采用概率可靠性理论对结构件的失效风险进行量化分析，为设计阶段的优化提供了科学依据。结果表明，所提方法能够准确捕捉焊接结构件在不同工况下的疲劳行为，预测误差控制在5%以内，且相较于传统方法具有更高的鲁棒性和适应性。该研究的创新点在于将数据驱动与物理机制相结合，实现了从单一经验公式向智能化预测模型的转变，为焊接结构件的设计与维护提供了新思路。研究成果可为相关领域的工程应用提供重要参考价值。
关键词：焊接结构件；疲劳寿命预测；多源数据融合；机器学习；可靠性评估
Abstract
Welded structural components are widely used in aerospace, shipbuilding, and civil engineering, where their fatigue life and reliability directly affect the safety and economy of systems. However, traditional fatigue life prediction methods exhibit significant errors under complex stress states and multi-factor coupling conditions, failing to meet engineering requirements. To address this issue, this study proposes a fatigue life prediction and reliability evaluation method for welded structures based on multi-source data fusion. By integrating finite element analysis with experimental testing, a fatigue damage model is established that considers residual stresses, microstructural inhomogeneities, and load spectrum effects. Machine learning algorithms are introduced to optimize model parameters, thereby significantly improving prediction accuracy. Simultaneously, probabilistic reliability theory is employed to quantitatively analyze the failure risk of structural components, providing a scientific basis for optimization during the design phase. Results indicate that the proposed method accurately captures the fatigue behavior of welded structures under various operating conditions, with prediction errors controlled within 5%, demonstrating higher robustness and adaptability compared to conventional methods. The innovation of this research lies in combining data-driven approaches with physical mechanisms, achieving a transition from single empirical formulas to intelligent predictive models, thus offering new insights for the design and maintenance of welded structures. The findings provide valuable references for engineering applications in related fields.
Keywords：Welded Structural Components; Fatigue Life Prediction; Multi-Source Data Fusion; Machine Learning; Reliability Assessment
目 录
摘要 I
Abstract II
一、绪论 1
(一) 焊接结构件疲劳寿命预测的研究背景与意义 1
(二) 国内外焊接结构件疲劳寿命预测研究现状 1
(三) 本文研究方法与技术路线 2
二、焊接结构件疲劳损伤机理分析 2
(一) 焊接残余应力对疲劳性能的影响 2
(二) 焊接缺陷对疲劳裂纹扩展的作用 3
(三) 材料特性与焊接工艺的关联性研究 3
三、焊接结构件疲劳寿命预测模型构建 4
(一) 基于断裂力学的疲劳寿命预测方法 4
(二) 数据驱动的疲劳寿命预测模型开发 4
(三) 不同工况下疲劳寿命预测模型的验证 5
四、焊接结构件可靠性评估方法研究 6
(一) 可靠性评估的基本理论与框架 6
(二) 疲劳寿命不确定性对可靠性的影响 6
(三) 基于概率统计的可靠性评估模型构建 7
结 论 8
参考文献 9
