This paper proposes an efficient and reliable modeling method to address the longstanding reliance on empirical expertise and the lack of systematic theoretical guidance in the design of pipeline permanent magnet in-line inspection tools. This method accurately characterizes the localized saturation magnetic field and the coupling mechanism with pipeline wall defects, enabling a quantitative analysis of the inspection performance. On the basis of the traditional magnetic circuit method, the theory of magnetic field segmentation is introduced, and an improved magnetic network model suitable for internal detection of pipeline leakage is constructed. The model fully considers the edge effect and the nonlinear magnetization characteristics of ferromagnetic materials, combining the key parameters of the detection device with the magnetic leakage field caused by defects. The internal relationship between the two is revealed, and then the quantitative calculation of the dynamic evolution process and spatial distribution of the local saturated magnetic field is realized. The improved magnetic network method proposed in this study shows good versatility and model adaptability while ensuring high computational efficiency. In order to verify its effectiveness, finite element numerical simulation and experiments were carried out respectively, and the calculation results of the model were compared and analyzed. The results show that the improved magnetic network model aligns well with the finite element simulation results in terms of magnetic field distribution characteristics and key signal response, with an error controlled within 5%. Compared to experimental measurement results, the overall relative error is less than 30%, demonstrating acceptable accuracy for engineering applications. The model effectively captures the magnetic field disturbances caused by inner wall defect, accurately reflecting their influence on the output performance parameters of the detection device, thereby compensating for the shortcomings of traditional magnetic circuit design theory. The proposed method exhibits both high computational accuracy and efficiency, making it suitable for the rapid performance evaluation and iterative optimization design of in-line inspection devices in engineering practice. Moreover, it provides a reliable theoretical basis and model support for the parameter design, performance prediction, and engineering applications of such equipment.