| 基于粒子群最大似然估计的焊缝早期隐性损伤磁记忆精确定位模型 |
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| 作者姓名： | 邢海燕 陈思雨 李思岐 葛桦 孙晓军 |
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| 作者单位： | 东北石油大学机械科学与工程学院,大庆,163318;哈尔滨工业大学航天学院,哈尔滨,150001 |
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| 基金项目： | 东北石油大学研究生创新科研项目资助(YJSCX2016-024NEPU)中国石油科技创新基金资助项目(2015D-5006-0602)国家自然科学基金资助项目(11272084,11072056,11472076)中国石油和化学工业联合会科技指导计划资助项目(2017-01-05) |
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| 摘 要： | 针对由于焊接残余应力、磁场噪声等干扰,造成磁记忆检测在焊缝早期隐性损伤位置定量评价上的困难,提出基于粒子群算法优化的最大似然估计磁记忆梯度定量模型.通过对预制未焊透缺陷的Q235焊接试件进行焊缝疲劳拉伸实验,同步对比扫描电镜和X射线检测结果,发现磁记忆信号梯度对早期隐性损伤位置反应比较敏感,并获得了梯度随着与隐性损伤的距离增大而减小的衰减变化规律,构建隐性损伤位置参数与磁记忆梯度的非线性函数,考虑磁场噪声对隐性损伤定位结果的影响,引入最大似然估计建立目标函数,进一步考虑目标函数的非线性容易陷入局部极值而非全局极值的问题,采用具有全局搜索能力的粒子群算法对目标函数进行优化,建立基于粒子群最大似然估计的焊缝隐性损伤位置磁记忆定量模型,验证结果表明定位误差仅为3.48%,为实际工程中利用磁记忆技术及时发现早期隐性损伤并精确定位提供了新的思路.
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| 关 键 词： | 磁记忆 最大似然估计 梯度 粒子群算法 损伤定位 |
| 收稿时间： | 2017-03-12 |
MMM accurate location model of early hidden damage in welded joints based on PSO and MLE |
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| Affiliation: | 1) School of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, China2) School of Astronautics, Harbin Institute of Technology, Harbin 150001, China |
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| Abstract: | To accurately locate hidden damage in welded joints, a metal magnetic memory (MMM) gradient model was present based on maximum likelihood estimation (MLE) optimized by particle swarm optimization (PSO). Tabular welded Q235 specimens were subjected to fatigue tensile experiments. Using electron microscope scanning and X-ray detection, it is found that MMM gradient K is sensitive to the location of early hidden damage and decreases with an increase in distance from it. A nonlinear function is then presented between the position parameter and the MMM gradient. MLE is introduced to establish the nonlinear objective function. Furthermore, considering the nonlinear objective function is easy to get into the local rather than the global extremum, the PSO is adopted to optimize the objective function for a global search ability. The results show the location error of the model is 3.48%, therefore MMM provides a new tool for the identification and accurate location of early hidden damage in welded joints. |
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