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降低电极接地电阻的方法 被引量:4
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作者 彭智波 黄振峰 《现代电子技术》 2011年第21期208-210,共3页
介绍影响电极接地电阻的因素,通过分析影响土壤电阻率的因素及接地电极与接地电阻值间的关系,总结了通过降低土壤电阻率与改进接地电极两种类别总共七种降低接地电阻的方法,为需要进行电极接地的电法类检测及测试提供参考和选择。
关键词 接地 接地 土壤阻率 电法类检测
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Prediction study of hydrocarbon reservoir based on time-frequency domain electromagnetic technique taking Ili Basin as an example 被引量:1
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作者 Tian Yu-Kun Zhou Hui +1 位作者 Ma Yan-Yan Li Juan 《Applied Geophysics》 SCIE CSCD 2020年第5期687-699,900,901,共15页
The time-frequency domain electromagnetic(TFEM)sounding technique can directly detect oil and gas characteristics through anomalies in resistivity and polarizability.In recent years,it has made some breakthroughs in h... The time-frequency domain electromagnetic(TFEM)sounding technique can directly detect oil and gas characteristics through anomalies in resistivity and polarizability.In recent years,it has made some breakthroughs in hydrocarbon detection.TFEM was applied to predict the petroliferous property of the Ili Basin.In accordance with the geological structure characteristics of the study area,a two-dimensional layered medium model was constructed and forward modeling was performed.We used the forward-modeling results to guide fi eld construction and ensure the quality of the fi eld data collection.We used the model inversion results to identify and distinguish the resolution of the geoelectric information and provide a reliable basis for data processing.On the basis of our results,key technologies such as 2D resistivity tomography imaging inversion and polarimetric constrained inversion were developed,and we obtained abundant geological and geophysical information.The characteristics of the TFEM anomalies of the hydrocarbon reservoirs in the Ili Basin were summarized through an analysis of the electrical logging data in the study area.Moreover,the oil-gas properties of the Permian and Triassic layers were predicted,and the next favorable exploration targets were optimized. 展开更多
关键词 Time–Frequency Domain Electromagnetic Hydrocarbon Detection Polarizability Anomaly Favorable Area Prediction
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A Transmission Line Fault Classification Approach by Support Vector Machines
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作者 A.M. Ibrahim A.Y. Abdelaziz S.F. Mekhamer M. Ramadan 《Journal of Energy and Power Engineering》 2011年第3期268-274,共7页
This paper presents an approach for shunt faults detection and classification in transmission line using Support Vector Machine (SVM). The paper compares between using three line post-fault current samples for one-h... This paper presents an approach for shunt faults detection and classification in transmission line using Support Vector Machine (SVM). The paper compares between using three line post-fault current samples for one-half cycle and one-fourth cycle from the inception of the fault as inputs for SVM. Two SVMs are used, first SVMabc is used for faulty phase detection and second SVMg is used for ground detection. SVMs with polynomial kernel with different degrees are used to obtain the best classification score. The classification test results show that the proposed method is accurate and reliable. 展开更多
关键词 Transmission line protection fault detection fault classification support vector machine.
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