去除漏磁数据中无缝管道噪声的小波域自适应滤波算法

漏磁(MFL)检测是油气管道在线检测中应用非常成熟的一种无损检测技术。将小波变换与自适应滤波技术相结合,提出了一种去除漏磁数据中无缝管道噪声(SPN)的小波域自适应滤波算法。将该算法用于实测漏磁数据的处理,所得结果说明该算法具有良好的去噪效果,可以极大地提高漏磁数据中缺陷信号的可检测性。

Wavelet transform domain adaptive filtering algorithm for removing the seamless pipe noise contained in the magnetic flux leakage data

Magnetic flux leakage (MFL) inspection is a most successful non-destructive evaluation technique used for in-service inspection of pipelines. By combining wavelet transform with adaptive filtering technique, a new algorithm called wavelet transform domain adaptive filtering was proposed for removing the seamless pipe noise (SPN) contained in the MFL data. The algorithm was applied to the MFL data obtained from field tests. The results demonstrate the effectiveness of the algorithm. The algorithm has good performance and considerably improves the detectability of the defect signals in the MFL data.