基于改进AHP模型的城市轨道交通车体吊挂梁结构可靠性优化方法

Reliability Optimization Method for Urban Rail Transit Car Body Suspension Beam Structures Based on Improved AHP Model

  • 摘要:
    目的 城市轨道交通车体吊挂梁结构的服役可靠性,直接影响车辆系统服役安全性及可靠性。为提升车体吊挂梁结构服役可靠性水平,提出一种基于准则相关性层次分析法模型的城市轨道交通车体吊挂梁结构可靠性优化方法。
    方法 利用参数化分析方法开展运用工况条件下的结构性能分析。根据分析结果及概率化相关性量化法则,统计结构设计方案与顶层设计目标的相关性矩阵,并根据传统AHP评估模型构建设计准则层的权重矩阵,进而利用矩阵相乘原理完成相关性权重矩阵的构建。在保证相关性权重矩阵满足一致性比率要求的条件下,建立结构可靠性优化模型,利用优化算法开展结构可靠性优化设计。以某城市轨道交通车体吊挂梁结构为例,验证了所提方法的有效性。
    结果及结论  所提方法可合理分配各结构设计准则的相关性权重,并使城市轨道交通车体吊挂梁结构失效概率降至0.001 9。

     

    Abstract:
    Objective Service reliability of the car body suspension beam structure in urban rail transit directly affects the service safety and reliability of the vehicle system. To improve this service reliability, a reliability optimization method for urban rail transit car body suspension beam structures is proposed based on a criterion-correlation analytic hierarchy process (AHP) model.
    Method A parametric analysis method is used to analyze the structural performance under operating conditions. According to the analysis results and the quantitative rule of probabilistic correlation, a correlation matrix between the structural design scheme and the top-level design objectives is established. Combined with the traditional AHP evaluation model, the weight matrix of the design criterion layer is constructed, and then a correlation weight matrix is formed using matrix multiplication. On the premise that the correlation weight matrix meets the requirement of consistency ratio, a structural reliability optimization model is established, and the structural reliability optimization design is carried out using an optimization algorithm. In case study of an urban rail transit car body suspension beam structure, the effectiveness of the proposed method is verified.
    Result & Conclusion The proposed method can reasonably allocate the correlation weights of each structural design criterion and reduce the failure probability of urban rail transit car body suspension beam structure to 0.0019.

     

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