摘要
为保障高速铁路行车安全,从铁磁性材料磁化的机理出发,分析漏磁检测的基本原理,介绍漏磁检测技术在钢轨缺陷检测中的应用研究,提出高速钢轨缺陷的漏磁检测方法。采用有限元法建立缺陷漏磁检测模型,分析缺陷漏磁场Bx、By和Bz分量的特点,并针对高速钢轨漏磁检测中缺陷提取相应的特征参数,运用人工神经网络的方法实现漏磁检测缺陷的反演,取得较好的反演结果。
To ensure the security of high speed railway,the basic principle of magnetic flux leakage detection was analyzed from the standpoint of magnetizing mechanism of ferromagnetism materials.The application of the current defects detecting technologies in high speed rails based on magnetic flux leakage was introduced and one test method based on magnetic flux leakage was proposed to detect defects in high speed rails.In order to overcome the shortcoming of traditional MFL measurement that uses the magnetic field density components in x-and z-axes,three dimensional(3D) pulsed magnetic leakage field measurements were proposed.According to the characteristic parameters of defects in the high speed rails,the method accomplished refutations of detecting defects based on magnetic flux leakage by means of neural network and got excellent results.
出处
《中国测试》
CAS
北大核心
2013年第1期22-24,42,共4页
China Measurement & Test
基金
国家自然科学基金项目(50907032/E070104)
关键词
漏磁检测
反演问题
神经网络
钢轨缺陷
magnetic flux leakage detection
refutation
neural network
defects of rail