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基于自然电场监测的金属污染物动态成像(英文)
Dynamic imaging of metallic contamination plume based on self-potential data
【摘要】 提出了自然电场数据的动态成像方法。基于达西定律和阿尔奇公式,构建模拟孔隙介质中金属离子运动的动态模型。采用能斯特方程计算金属离子的氧化还原电位。在此基础上建立自然电场监测金属离子活动的状态模型和观测模型,利用扩展卡尔曼滤波技术对金属离子活动过程进行动态成像。模拟数据测试结果表明,该方法能有效将金属离子运动模型与自然电场观测数据融合,实现动态成像。进一步沙箱监测实验表明,自然电场法可以有效监测金属离子污染,利用动态成像方法可以有效重构金属离子的扩散过程。
【Abstract】 A dynamic imaging method for monitoring self-potential data was proposed.Based on the Darcy’s law and Archie’s formulas,a dynamic model was built as a state model to simulate the transportation of metallic ions in porous medium,and the Nernst equation was used to calculate the redox potential of metallic ions for observation modeling.Then,the state model and observation model form an extended Kalman filter cycle to perform dynamic imaging.The noise added synthetic data imaging test shows that the extended Kalman filter can effectively fuse the model evolution and observed self-potential data.The further sandbox monitoring experiment also demonstrates that the self-potential can be used to monitor the activities of metallic ions and exactly retrieve the dynamic process of metallic contamination.
【Key words】 dynamic imaging; self-potential; metallic contamination; extended Kalman filter;
- 【文献出处】 Transactions of Nonferrous Metals Society of China ,中国有色金属学报(英文版) , 编辑部邮箱 ,2017年08期
- 【分类号】O657.1;X830
- 【下载频次】90