漏磁信号增强算法研究

对漏磁信号进行增强处理以提高其信噪比是实现漏磁数据智能分析的重要前提。漏磁信号中同时包含低频和高频噪声，直接进行处理往往会产生较高的错误率。从无限长矩形凹槽的磁偶极子模型中发现，漏磁场的切向分量和法向分量的原函数和一阶导数具有较强的交叉相关性。于是，利用这种交叉相关性，提出将漏磁场磁感应强度切向分量和法向分量融合的漏磁信号增强算法，对检测目标位置的信号进行增强，同时对其余位置的噪声进行抑制，从而提高漏磁信号的信噪比。利用牵拉实验数据和在役管道漏磁内检测数据对算法进行了初步验证和推广。最后，从在役管道漏磁内检测数据中收集了若干样本，并提出适合于漏磁信号的信号质量评估方法，对所提增强算法进行量化评估。实验结果显示，几乎所有样本的信号质量均得到了提高，大多数样本得到了不小于10 dB的提高。

Research on the MFL signal enhancement algorithm

To improve the signal noise ratio (SNR), it is important to enhance the intelligent analysis of MFL signal. If MFL data are processed directly, it usually has low precision due to the low and high frequency noise contained in MFL signal. It is discovered from the magnetic dipole model of infinite rectangular groove that there is a cross correlation between the original function and first derivative of the normal component and tangential component leakage magnetic field. Therefore, a MFL signal enhancement algorithm is proposed based on the cross correlation, which can enhance the signal near detect targets and suppress noise. Hence, the SNR of MFL signal is improved. The algorithm is validated and generalized by pipeline pull-through test data and in-service pipeline inspection data, respectively. Finally, some samples are collected from in-service pipeline inspection data and a signal quality estimation method is proposed which is suitable for evaluating the quality of the MFL signal. The enhancement algorithm is quantitatively evaluated by the samples and the estimation method. Experimental results show that almost all the samples are improved and most of the samples are improved by 10 dB at least.