In the traditional pipeline magnetic flux leakage (MFL) detection technology, circumferential or axial excitation is mainly used to excite the magnetic field of defects. However, the domestic and foreign pipeline detection devices currently in operation are mainly axial excitation MFL detection tools, in which circumferential cracks can be clearly identified, but the detection sensitivity of axial cracks is not high, thus forming a detection blind zone. Therefore, a composite excitation multi-extension direction defect MFL detection method is proposed, which can realize the simultaneous detection of axial and circumferential defects. On the basis of the electromagnetic theory Maxwell equation and Biot Savart law, a mathematical model of circumferential and axial magnetization is firstly established. Then finite element simulation software is used to establish a model of a new type of magnetic flux leakage detection device, and a simulation analysis of crack detection in multiple extension directions is carried out. Finally, under the conditions of the relationship model between the change rate of leakage magnetic field and external excitation intensity under unsaturated magnetization and the multi-stage coil magnetization model, the sample vehicle towing experiment is carried out. The paper aims to analyze the feasibility and effectiveness of the new magnetic flux leakage detection device for detecting defects in different extension directions. Based on the final experimental results, the new composite excitation multi extension direction leakage magnetic field detector has a good detection effect for defects in the axial and circumferential extension directions.

The collection of magnetic anomaly signal underground pipelines is disturbed by environmental noise. The wavelet threshold method is used as the basic denoising model of the magnetic anomaly signal of underground pipelines, and a composite normalization index is added on the basis of the traditional evaluation index to optimize the wavelet basis functions, optimal decomposition scale and threshold function. An improved threshold function with tunable variable genes is determined to make up for the lack of breakpoint oscillations and loss details of traditional soft and hard threshold function estimation methods. The denoising and effect evaluation of the noisy magnetic anomaly signal is carried out through the simulation signal and experiment. The simulation and experimental results show that the improved threshold function can effectively eliminate the interference of the surrounding noise on the magnetic anomaly signal, and then accurately restore the original magnetic anomaly signal compared with conventional methods, the extracted signal has less distortion and higher SNR, which can provide more accurate data support for subsequent magnetic anomaly inversion.