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基于有限元建模的管道腐蚀热成像检测方法

发表时间:2019-10-31  浏览量:2562  下载量:284
全部作者: 赵勋,胡建中
作者单位: 东南大学机械工程学院
摘 要: 管道运输由于具有高效、经济、便利等特点在生活中被广泛使用,但管道长期使用后极易形成内壁腐蚀缺陷,导致性能降低,引发事故。本文提出一种基于有限元建模的管道腐蚀热成像检测方法。在建立腐蚀管道温度场有限元模型的基础上,利用ANSYS软件计算通入恒温流体时管道表面温度场分布的变化,通过分析不同温度流体下管道表面温度分布的变化序列,构建了基于热成像序列的腐蚀管道缺陷检测模型。通过红外热成像仪获取管道表面热图像序列,实现管道腐蚀缺陷的在线检测。研究搭建了管道腐蚀检测实验台,实验结果表明,基于有限元模型的红外热成像检测方法可以快速、有效地实现管道腐蚀的无损检测。
关 键 词: 机械制造自动化;管道;有限元;热成像;腐蚀
Title: Pipeline corrosion thermal imaging detection method based on finite element modeling
Author: ZHAO Xun, HU Jianzhong
Organization: School of Mechanical Engineering, Southeast University
Abstract: Pipeline transportation is widely used in life because of its high efficiency, economy, convenience, etc., but it is easy to form internal wall corrosion defects after long-term use, resulting in reduced performance of the pipeline and causing accidents. A pipeline corrosion thermal imaging detection method based on finite element modeling is presented in this paper. Based on the finite element model of the temperature field of the corroded pipeline, the ANSYS software was used to calculate the change of the temperature field distribution on the pipeline surface when the constant temperature fluid was inflowed. By analyzing the temperature distribution change sequence on the pipeline surface under different temperature fluids. A pipeline corrosion defect detection model was constructed based on thermal imaging sequence. The thermal image sequence on the pipeline surface was obtained by an infrared thermal imager to realize online detection of pipeline corrosion defects. A pipeline corrosion test bench was set up, and the experimental results showed that the infrared thermal imaging detection method based on the finite element model can quickly and effectively achieve non-destructive testing of pipeline corrosion.
Key words: mechanical manufacturing and automation; pipeline; finite element; thermal imaging; corrosion
发表期数: 2019年10月第5期
引用格式: 赵勋,胡建中. 基于有限元建模的管道腐蚀热成像检测方法[J]. 中国科技论文在线精品论文,2019,12(5):703-710.
 
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用户duantao0601:文章写的非常好,推荐推荐~

2020-03-28 21:03:50
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