基于智能视觉的混凝土微结构质量检测方法研究
Research on Concrete Micro Structure Analysis Based on Intelligent Vision

作者: 郑圣子 * , 李相旭 :天津科技大学机械工程学院;

关键词: 智能视觉混凝土模糊分类Intelligent Vision Concrete Fuzzy Classification

摘要:
混凝土质量对建筑物,桥梁,公路等设施的安全性,可靠性影响很大。目前的质量检测主要是人工的方法,通过显微镜观察混凝土切面的成分组成和分布,费时费力,检测质量很难保证。本文提出一种新颖的基于模糊规则混凝土质量智能视觉识别技术,通过支持向量机自动学习模糊规则,模仿人类的智能视觉识别过程,提高质量检测的自动化,可靠性和效率。实验证明,该方法相对于传统的方法来说,是有效的。

Abstract:
The quality of concrete plays an important role in assessing the safety and reliability issues of buildings, bridges and roads. At present, quality tests mainly depend on manual labor, through a micro telescope vision to check crossover of concrete sample. It is time-consuming and the test results have low reliability. This paper proposes a new intelligent vision based on analyzing method by implementing fuzzy logic. Base on support vector learning, the fuzzy rules are constructed automatically simulating a human learning and classifying process. This approach improves the productivity, reliability, and degree of automation. Compared with traditional method, this way proves its effectiveness through experimental verification.

文章引用: 郑圣子 , 李相旭 (2013) 基于智能视觉的混凝土微结构质量检测方法研究。 计算机科学与应用, 3, 267-271. doi: 10.12677/CSA.2013.35046

参考文献

[1] R. Pleau, M. Pigeon. Precision statement for ASTM C 457 practice for microscopical determination of air-void content and other parameters of the air-void system in hardened concrete. Cement, Concrete, and Aggregates, 1992, 14: 118-126.

[2] 杨鲁. 新拌混凝土和硬化混凝土气泡参数研究[D]. 重庆大学, 2012.

[3] 周博文, 保健酒智能视觉检测机器人技术研究[D]. 湖南大学, 2012.

[4] 马灿. PCB缺陷智能视觉检测系统研究与设计[D]. 湖南大学, 2012.

[5] 夏天煜. 在线智能视觉检测系统在小包装食盐装箱中的应用[J]. 北京工商大学学报(自然科学版), 2011, (5): 61-64.

[6] Y. Chen, J. Z. Wang. Support vector learning for fuzzy rule based classification system. IEEE Transaction on Fuzzy Systems, 2003, 11(6): 716-728.

[7] 李洪兴. 模糊控制的差值机理[J]. 中国科学, 1998, 28(3): 259-264.

[8] 张莉, 周伟达, 焦李成. 尺度核函数支持向量机[J]. 电子学报, 2002, 30(4): 527-529.

分享
Top