漏磁
希尔伯特-黄变换
噪音(视频)
管道(软件)
小波变换
无损检测
残余物
小波
计算机科学
声学
人工智能
泄漏(经济)
材料科学
计算机视觉
图像(数学)
算法
物理
磁场
滤波器(信号处理)
量子力学
经济
宏观经济学
程序设计语言
作者
Liang Chen,Jingcheng Li,Yakai Zeng,Yongqiang Chen,Wei Liang
标识
DOI:10.4283/jmag.2019.24.3.423
摘要
The magnetic flux leakage (MFL) method is the most widely used and cost-effective inspection technique for oil pipeline. However, noise is inevitable in the process of data collection; thus, the image enhancement method can be more intuitive to identify the defects in an oil pipeline MFL inspection. In this paper, the bidimensional empirical mode decomposition (BEMD) method has been used to study oil pipeline MFL images. The MFL image is decomposed into a finite number of two-dimensional intrinsic mode functions (BIMF) and a residual component by the BEMD. The wavelet transform (WT) was used to remove the noise in the BIMF. The image was then reconstructed by retaining the basic information and removing the noise. The results show that the noise is effectively removed and the detail of the MFL image is well preserved. Thus, the BEMD with WT method for oil pipeline MFL image enhancement is better than the mean filtering method and the WT method.
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