聚丙烯纤维再生混凝土主破裂前兆特征研究
Study on Main Fracture Precursor Characteristics of Polypropylene Fiber Recycled Concrete
杨欣 1唐宇 1梁宁慧2
作者信息
- 1. 福建理工大学土木工程学院,福州 350118;福建理工大学地下工程福建省高校重点实验室,福州 350118
- 2. 重庆大学土木工程学院,重庆 400045
- 折叠
摘要
为研究聚丙烯纤维再生混凝土的破裂尺度和主破裂前兆特征,设计制作了20组粗骨料替代率为25％和50％的试件,通过开展单轴压缩声发射试验,提取聚丙烯纤维再生混凝土破裂过程声发射能量和主频.以能量为媒介,探讨破裂尺度和声发射信号特征之间的对应关系.采用K-means聚类方法将大尺度破裂和小尺度破裂进行二维聚类分析,然后运用支持向量机得到大尺度破裂和小尺度破裂两类聚类的分界线.分析了聚丙烯纤维再生混凝土破裂过程声发射信号演化规律,发现存在声发射事件率减少,大尺度破裂信号增加,低能量小尺度破裂信号消失等特征.引入前兆响应系数概念,计算结果表明低能量小尺度破裂信号消失特征的前兆响应系数最大,前兆响应时间最早.
Abstract
In order to study the cracking scale and main fracture precursor characteristics of polypropylene fiber recycled concrete,20 groups of specimens with coarse aggregate replacement rates of 25％and 50％were designed and manufactured.Through the uniaxial compression acoustic emission test,the acoustic emission energy and main frequency of polypropylene fiber recycled concrete fracture process were extracted.Using energy as a medium,the correspondence between cracking scale and acoustic emission characteristics is discussed.In this paper,K-means clustering method is used to perform a two-dimensional cluster analysis of large scale cracking and small scale cracking,and then a support vector machine is used to obtain the boundary between large scale cracking and small scale cracking.The evolution law of acoustic emission signal in the fracture process of polypropylene fiber recycled concrete was analyzed.It was found that the acoustic emission event rate decreased,the large scale cracking signal increased,and the low-energy small scale cracking signal disappeared.The concept of main fracture precursor response coefficient is introduced.The calculation results show that the precursor response coefficient of the disappearance characteristics of low energy small scale cracking signal is the largest,whose precursor response time is the earliest.
关键词
聚丙烯纤维再生混凝土/声发射/破裂尺度/前兆特征/K-means聚类Key words
polypropylene fiber recycled concrete/acoustic emission/cracking scale/precursory characteristics/K-means clustering引用本文复制引用
基金项目
福建省自然科学基金(2022J01930)
出版年
2024
NETL
NSTL
万方数据