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摘要:
针对电阻抗断层成像(EIT)技术中FCM聚类算法的灵敏度系数信息缺失以及测量电压的利用率低两方面问题,提出一种新的成像算法。在该算法中引入灵敏度系数矩阵信息修正各个剖分单元的电压。同时提出了将测量电压数据按照其权系数进行处理的方法,该方法可应用于所有EIT经典反演算法之中。理论和数值仿真结果均表明,与已有的FCM聚类算法相比,优化后算法对两相流型的定位准确度更高,得到的重建图像的空间分辨率与之前相比相对误差降低了5%~15%,相关系数提高了5%~20%。
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关键词:
- 电阻抗断层成像(EIT) /
- FCM聚类算法 /
- 测量电压 /
- 灵敏度系数矩阵 /
- 两相流型
Abstract:This paper focuses on the lack of the sensitivity coefficient information and the low utilization of the measurement voltage in FCM clustering algorithm in electrical impedance tomography (EIT) technology, and proposes a new imaging algorithm. In the new algorithm, sensitivity matrix information is introduced to correct the voltage of each subdivision unit. And at the same time, we propose to handle the measurement voltage according to its weight coefficient in the total voltage value, and this method can be applied to all EIT classical inversion algorithms. Both the theoretical analysis and numerical simulation results demonstrate that the new algorithm is more accurate in locating two-phase flow patterns than the existing FCM clustering algorithm, the spatial resolution deviation of reconstructed image has been reduced by 5% to 15%, and the correlation coefficient has been increased by 5% to 20%.
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表 1 不同算法的4个模型重建图像
Table 1. Reconstructed images for four models by different algorithms
模型序号 两相流模型 LBP算法 FCM-EIT算法 优化后FCM-EIT算法 1 2 3 4 表 2 Landweber和Tikhonov算法及权系数法的模型重建图像
Table 2. Model reconstructed images by Landweber and Tikhonov algorithms and coefficient weighting
泡状介质分布模型 Landweber/Tikhonov算法成像 权系数法处理后成像 表 3 LBP、原始图像、优化后图像的相关系数
Table 3. Correlation coefficients of LBP, original image and optimized image
模型序号 LBP算法 原始FCM算法 优化后FCM算法 1 0.414 1 0.364 7 0.415 4 2 0.373 8 0.295 9 0.390 2 3 0.166 9 0.877 7 0.922 2 4 0.345 5 0.405 1 0.568 4 表 4 LBP、原始图像、优化后图像的相对误差
Table 4. Relative errors of LBP, original image and optimized image
模型序号 LBP算法 原始FCM算法 优化后FCM算法 1 0.173 4 0.276 3 0.201 1 2 0.207 7 0.267 8 0.163 9 3 0.859 8 0.072 8 0.050 5 4 0.301 2 0.297 8 0.219 5 -
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