漏磁检测的混合正则化反演方法研究

漏磁检测作为无损检测的主要方法之一已得到了广泛关注和应用。漏磁检测对缺陷的识别问题属于电磁场计算的反问题,因其不适定性难以直接求解,因此目前对于漏磁检测方法的研究和应用大部分都避免了对反问题直接求解,而是采用搜索匹配式的方法。文中尝试使用混合正则化LSQR-Tikhonov的方法对基于磁偶极子单元积分模型的漏磁检测反演问题进行处理,对LSQR方法添加Tikhonov正则化来获得更多的主奇异值信息减小误差,通过混合正则化计算得到的近似解较为逼近真实值,得到的二维反演结果也可以判断出缺陷的位置和形状,通过仿真及实验验证了算法的准确性。

Research on hybrid regularization inversion method for magnetic flux leakage detection

Magnetic flux leakage detection has received extensive attention and application as one of the main methods of non-destructive testing. The problem of identification of defects by magnetic flux leakage detection belongs to the inverse problem of electromagnetic field calculation. It is difficult to directly solve the problem due to its ill-posedness. Therefore, at present, most of the research and application of magnetic flux leakage detection methods are to avoid the search matching method which directly solves the inverse problem. The method of mixed regularization LSQR-Tikhonov is used to deal with the magnetic flux leakage detection inversion problem based on the magnetic dipole unit integration model. Add Tikhonov regularization to the LSQR method to obtain more main singular value information to reduce the error. The approximate solution obtained by regularization is closer to the true value, and the reflected two-dimensional inversion results can also determine the position and shape of the defect. The accuracy of the algorithm is verified by simulation and experiment.