华南理工大学学报(自然科学版) ›› 2025, Vol. 53 ›› Issue (12): 107-116.doi: 10.12141/j.issn.1000-565X.250203

• 结构安全 • 上一篇    下一篇

基于Fisher变换和Bayes分类原理的RC梁柱中节点破坏形态多参数判别方法

王素裹1, 范存喜1, 郑宜2   

  1. 1.福州大学 土木工程学院,福建 福州 350108
    2.建同设计有限公司,广东 广州 511466
  • 收稿日期:2025-07-03 出版日期:2025-12-25 发布日期:2025-08-15
  • 作者简介:王素裹(1984—),女,博士,副教授,主要从事结构设计理论、结构抗震研究。E-mail: wangsuguo@foxmail.com
  • 基金资助:
    福建省自然科学基金项目(2024J01355);福建省自然科学基金项目(2018J01770)

A Multi-Parameter Discrimination Method for Failure Modes of RC Beam-Column Joints Based on Fisher Transform and Bayes Classification Principle

WANG Suguo1, FAN Cunxi1, ZHENG Yi2   

  1. 1.College of Civil Engineering,Fuzhou University,Fuzhou 350108,Fujian,China
    2.Jian Tong Consulting Group,Guangzhou 511466,Guangdong,China
  • Received:2025-07-03 Online:2025-12-25 Published:2025-08-15
  • About author:王素裹(1984—),女,博士,副教授,主要从事结构设计理论、结构抗震研究。E-mail: wangsuguo@foxmail.com
  • Supported by:
    the Natural Science Foundation of Fujian Province(2024J01355)

摘要:

钢筋混凝土梁柱节点在侧向荷载作用下的多种不同破坏形态对结构性能具有不同的影响,因此准确划分构件的破坏形态是结构性能设计中确定构件变形性能限值的关键。现有研究对梁柱节点不同破坏形态之间尚未明确划分界限,且难以通过单一参数区分出不同破坏类型对应的区间。基于Fisher变换和Bayes分类原理提出了一种能更准确、更方便应用的考虑多参数影响的梁柱中节点破坏形态判别方法。该方法先通过Fisher判别法寻找类与类最大分离的投影空间,将原样本向最大分离空间投影,从而获得更利于分类的新样本;在此基础上,进一步结合Bayes分类原理对新样本进行分类判别。在中节点破坏形态划分研究中,基于此分类方法,在选取轴压比、剪压比、混凝土强度和配箍特征值4个参数组合的基础上,建立了相应的多参数分类判别方程,达到了较好划分出梁柱中节点破坏形态和明确不同破坏形态对应的区间的目的。此外,还通过对影响因素的敏感性分析,确定了剪压比对梁柱中节点破坏形态的影响权重最大、配箍特征值次之,因此,调整剪压比和配箍特征值是避免该节点产生剪切破坏的有效途径。

关键词: 钢筋混凝土, 梁柱中节点, Fisher变换, Bayes分类, 破坏形态

Abstract:

The various failure modes of reinforced concrete (RC) beam-column joints under lateral loading exert different impacts on the structural performance. Thus, accurately categorizing component failure modes is pivotal for determining the deformation performance limits in structural performance design. Existing research lacks clear boundaries between different failure modes of beam-column joints, and it remains difficult to distinguish intervals corresponding to distinct failure types using a single parameter. This paper proposes a more accurate and practical discriminant method for identifying failure modes in interior beam-column joints, incorporating multiple parameters based on the Fisher transform and Bayes classification principles. The method initially employs the Fisher discriminant analysis to identify projection spaces with maximum separation between classes, projecting original samples into these optimally separated spaces to obtain new samples more amenable to classification. Subsequently, Bayes classification principles are applied for discriminant analysis of the new samples. In studying interior joint failure mode classification, based on this method the corresponding multi-parameter classification discriminant equations are established using a combination of four parameters: axial compression ratio, shear compression ratio, concrete strength, and stirrup characteristic value. This approach effectively classifies failure modes of interior beam-column joints and clearly defines intervals corresponding to different failure types. Furthermore, through sensitivity analysis of influencing factors, the study determines that the shear compression ratio has the most significant influence on failure modes, followed by the stirrup characteristic value. Therefore, adjusting the shear compression ratio and the stirrup characteristic value is an effective means of preventing shear failure at this type of joint.

Key words: reinforced concrete, beam-column joints, Fisher transform, Bayes classification, failure mode

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