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。
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.
出处
《计算机科学与应用》
2013年第5期267-271,共5页
Computer Science and Application
