清华四川能源互联网研究院油气新技术研究中心,610213,成都
四川大学深地工程智能建造与健康运维全国重点实验室,610065,成都
国家管网集团储运技术发展有限公司完整性技术中心,300457,天津
西安交通大学复杂服役环境重大装备结构强度与寿命全国重点实验室,710049,西安
作者简介:刘来鹏(2004-),男,本科生;
李红梅(通信作者),女,教授,博士生导师。
收稿:2025-12-23,
网络首发:2026-04-27,
纸质出版:2026-08-10
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针对电磁无损检测中传统二维模型难以准确反演三维立体结构内部磁化场分布的问题,提出了一种适用于平板和管状构件的三维磁荷分布反演方法。基于等效磁荷模型,推导了离散的三维磁化场分布控制方程;引入空间平滑性约束改进最小二乘优化目标,抑制反演结果的非物理振荡;结合Tikhonov正则化处理不适定问题,构建自适应梯度约束最小二乘反演算法;通过平板和管状模型仿真验证,预设三维正态磁化场分布,得到探测面的磁感应强度,再引入白噪声模拟含干扰的探测信号。采用所提算法对模拟信号进行反演,结果表明:平板模型与预设值的决定系数达0.9941,峰值相对误差最大为4.925%;管状模型内环/外环探测面的反演决定系数均超0.9972,峰值相对误差最大为2.406%;噪声干扰下的误差可控,鲁棒性较强。该方法改善了传统二维模型的局限性,可为后续应力分布反演及结构安全评估提供理论和算法基础,支撑基础设施的无损检测需求。
Traditional two-dimensional models fail to accurately invert the internal magnetization field distribution of 3D structures in electromagnetic nondestructive testing. To solve this problem
a three-dimensional magnetic charge distribution inversion method was proposed for plate and tubular components. Firstly
discretized governing equations for 3D magnetization field distribution were derived based on the equivalent magnetic charge model. Secondly
spatial smoothness constraints were adopted to optimize the least-squares objective function and suppress non-physical oscillations in the inversion results. Thirdly
Tikhonov regularization was introduced to solve ill-posed problems
and an adaptive gradient-constrained least-squares inversion algorithm was developed. Finally
numerical simulations of plate and tubular models were conducted. A preset 3D normal magnetization field was adopted to calculate the magnetic induction intensity on detection surfaces
and white noise was added to simulate interference-contained detection signals. The simulated signals were inverted by the proposed algorithm. The results show that the coefficient of determination between inverted values and preset parameters of the plate model reaches 0.9941
with a maximum peak relative error of 4.925%.For the tubular model
the coefficient of determination of inversion results on both inner and outer ring detection surfaces is higher than 0.997
and the maximum peak relative error is only 2.406%.The method maintains controllable errors under noise interference and presents excellent robustness. The approach presented in this paper overcomes the limitations of conventional 2D inversion methods. It provides theoretical support and algorithmic references for subsequent stress distribution inversion and structural safety evaluation
and satisfies the engineering requirements of nondestructive testing for infrastructure.
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