This paper proposed a method to generate semi-experimental biomedical datasets based on full-wave simulation software.The system noise such as antenna port couplings is fully considered in the proposed datasets,which ...This paper proposed a method to generate semi-experimental biomedical datasets based on full-wave simulation software.The system noise such as antenna port couplings is fully considered in the proposed datasets,which is more realistic than synthetical datasets.In this paper,datasets containing different shapes are constructed based on the relative permittivities of human tissues.Then,a back-propagation scheme is used to obtain the rough reconstructions,which will be fed into a U-net convolutional neural network(CNN)to recover the high-resolution images.Numerical results show that the network trained on the datasets generated by the proposed method can obtain satisfying reconstruction results and is promising to be applied in real-time biomedical imaging.展开更多
Petroleum production logging needs to determine the interpretation models first and flow pattern identification is the foundation, but traditional flow pattern identification methods have some limitations. In this pap...Petroleum production logging needs to determine the interpretation models first and flow pattern identification is the foundation, but traditional flow pattern identification methods have some limitations. In this paper, a new method of flow pattern identification in oil wells by electromagnetic image logging is proposed. First, the characteristics of gas-water and oil-water flow patterns in horizontal and vertical wellbores are picked up. Then, the continuous variation of the two phase flow pattern in the vertical and horizontal pipe space is discretized into continuous fluid distribution models in the pipeline section. Second, the electromagnetic flow image measurement responses of all the eight fluid distribution models are simulated and the characteristic vector of each response is analyzed in order to distinguish the fluid distribution models. Third, the time domain changes of the fluid distribution models in the pipeline section are used to identify the flow pattern. Finally, flow simulation experiments using electromagnetic flow image logging are operated and the experimental and simulated data are compared. The results show that the method can be used for flow pattern identification of actual electromagnetic image logging data.展开更多
In this article, a topological sensitivity framework for far-field detection of a diamet- rically small electromagnetic inclusion is established. The cases of single and multiple measurements of the electric far-field...In this article, a topological sensitivity framework for far-field detection of a diamet- rically small electromagnetic inclusion is established. The cases of single and multiple measurements of the electric far-field scattering amplitude at a fixed frequency are tak- en into account. The performance of the algorithm is analyzed theoretically in terms of its resolution and sensitivity for locating an inclusion. The stability of the framework with respect to measurement and medium noises is discussed. Moreover, the quantitative results for signal-to-noise ratio are presented. A few numerical results are presented to illustrate the detection capabilities of the proposed framework with single and multiple measurements.展开更多
基金National Natural Science Foundation of China(No.61971036)Fundamental Research Funds for the Central Universities(No.2023CX01011)Beijing Nova Program(No.20230484361)。
文摘This paper proposed a method to generate semi-experimental biomedical datasets based on full-wave simulation software.The system noise such as antenna port couplings is fully considered in the proposed datasets,which is more realistic than synthetical datasets.In this paper,datasets containing different shapes are constructed based on the relative permittivities of human tissues.Then,a back-propagation scheme is used to obtain the rough reconstructions,which will be fed into a U-net convolutional neural network(CNN)to recover the high-resolution images.Numerical results show that the network trained on the datasets generated by the proposed method can obtain satisfying reconstruction results and is promising to be applied in real-time biomedical imaging.
文摘Petroleum production logging needs to determine the interpretation models first and flow pattern identification is the foundation, but traditional flow pattern identification methods have some limitations. In this paper, a new method of flow pattern identification in oil wells by electromagnetic image logging is proposed. First, the characteristics of gas-water and oil-water flow patterns in horizontal and vertical wellbores are picked up. Then, the continuous variation of the two phase flow pattern in the vertical and horizontal pipe space is discretized into continuous fluid distribution models in the pipeline section. Second, the electromagnetic flow image measurement responses of all the eight fluid distribution models are simulated and the characteristic vector of each response is analyzed in order to distinguish the fluid distribution models. Third, the time domain changes of the fluid distribution models in the pipeline section are used to identify the flow pattern. Finally, flow simulation experiments using electromagnetic flow image logging are operated and the experimental and simulated data are compared. The results show that the method can be used for flow pattern identification of actual electromagnetic image logging data.
文摘In this article, a topological sensitivity framework for far-field detection of a diamet- rically small electromagnetic inclusion is established. The cases of single and multiple measurements of the electric far-field scattering amplitude at a fixed frequency are tak- en into account. The performance of the algorithm is analyzed theoretically in terms of its resolution and sensitivity for locating an inclusion. The stability of the framework with respect to measurement and medium noises is discussed. Moreover, the quantitative results for signal-to-noise ratio are presented. A few numerical results are presented to illustrate the detection capabilities of the proposed framework with single and multiple measurements.
