Big data technology is more and more widely used in modern power systems. Efficient collection of big data such as equipment status, maintenance and grid operation in power systems, and data mining are the important research topics for big data application in smart grid. In this paper, the application of big data technology in fast image recognition of transmission towers which are obtained using fixed-wing unmanned aerial vehicle (UAV) by large range tilt photography are researched. A method that using fast region-based convolutional neural networks (Rcnn) convolutional architecture for fast feature embedding (Caffe) to get deep learning of the massive transmission tower image, extract the image characteristics of the tower, train the tower model, and quickly recognize transmission tower image to generate power lines is proposed. The case study shows that this method can be used in tree barrier modeling of transmission lines, which can replace artificial identification of transmission tower, to reduce the time required for tower identification and generating power line, and improve the efficiency of tree barrier modeling by around 14.2%.
The purpose of this work is to study the electrochemical behavior of uranium and cerium in fused In/3LiCl-2KCl system in the temperature range of 723-823 K by open-circuit potentiometry. The apparent electrode potential of Ce 3+ /Ce (U 4+ /U) couples and apparent standard potential of Ce-In (U-In) alloys vs AgCl/Ag reference electrode were established. The principal thermodynamic properties, activity and solubility of cerium and uranium were determined. The separation factor of uranium/cerium couple on liquid indium electrode was calculated. The experimental results have been shown that a lower temperature should be more effective for the separation uranium from cerium.
Purification of rare earth elements is challenging due to their chemical similarities. The interaction and behavior of alloys involving stannous chloride (SnCl 2 ) and lanthanide metals are discussed in the present paper. We investigate the quantitative relationship between the deposition potential of lanthanides with SnCl 2 and atomic radius by employing electrochemical techniques, involving cyclic voltammetry (CV), square wave voltammetry (SWV) and open-circuit chronopotentiometry (OCP). Our electrochemical study on the formation intermetallic compounds is based on Sn in LiCl−KCl melts on molybdenum electrodes at 873 K. With the same experimental conditions, different deposits (e.g., Sn−La, Sn−Pr, Sn− Gd, Sn−Dy and Sn−Er) were obtained by using identical substrates. We establish the relationship between the deposition potential and the atomic radii of lanthanides by deriving a mathematical equation from the sorting out and summarizing of the data. The predictions for the existence and the deposition potentials of unknown intermediate phases (e.g., Sn−Ce, Sn−Nd, Sn−Yb and Sn−Lu) were made. From our results, open-circuit chronopotentiometry is potentially a valuable methodology to formally verify the correctness of the forecast. X-ray diffraction pattern (XRD), scanning electron micrograph (SEM) and energy-dispersive spectrometry (EDS) data further verify the reliability of the linear equation.
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