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The pose estimation of uncooperative target spacecraft is a key technique in on-orbit servicing missions, among which the method based on monocular camera with low mass and power requirements has attracted widespread attention. However, monocular pose estimation methods mostly rely on the known 3D model of the target spacecraft, and non-model-based methods have low accuracy and even output the results when there is no target spacecraft in the image. In this paper, a non-model-based monocular pose estimation network for uncooperative spacecraft based on the convolutional neural network is proposed. This network uses three sub-networks to solve the problems of pose estimation and object detection. The first sub-network, called the attitude prediction sub-network, is used to predict the relative attitude of the target spacecraft by soft classification and error quaternion regression. The second sub-network, called the position regression sub-network, is used to predict the relative position of the target spacecraft by regression. The third sub-network called the object detection sub-network is used to detect the target spacecraft to determine whether the predicted pose needs to be output. The experimental results of the pose estimation of two public spacecraft demonstrate that the proposed method can effectively detect the target spacecraft and achieve better pose estimation accuracy than previous non-model-based methods.

Biconvex tube is prone to problems such as severe wall thickness reduction or wrinkling in hydroforming due to the big diameter-thickness ratio and large expansion ratio. In this paper, the segmented dies were employed to manufacture the biconvex tube, and the forming performance of the part under different loading paths was simulated by ABAQUS/Explicit software, then the corresponding results were obtained. The influence of loading path–related factors on the formability of the biconvex tube was analyzed by the response surface method. Based on the optimization evaluation criteria, the predicted loading path was determined to be linear loading, and the maximum axial feeding was 13 mm and the maximum internal pressure was 89 MPa.

In China, the western energy base is far away from the eastern load center, therefore, long distance and large capacity transmission power grid gradually become the inevitable trend of development, and make a significant contribution to the construction of the global energy internet. 1000kV UHVAC transmission project has a profound and significant impact on the economic benefits, social environment, natural environment, ecological environment and future development. In this paper, an example has been taken for 1000kV UHVAC transmission project which is Inner Mongolia construction and management. By analyzing the environmental features of Inner Mongolia, the environmental impact evaluation index system has been established which is suit for the area, and provided the strongest support for subsequent UHV project.

In this paper, a method about design and implementation of centralized control in HVDC(high voltage direct current) is proposed. Using the method, the centralized control center can be completed in a relatively short period of time. And the equipments in each stations can be monitored and controlled very effectively var the computers in the centralized control center. In this way, we can save more human and material resources of the convert station, and improve the efficiency of the monitoring and controlling. The method conforms to the strategic thought of "Three Intensifications Five Systems" of National Grid. ( intensive management in human, financial and material resources, and systemic management in planning, construction, operation, maintenance and production).

In this paper, the design process of Three Phase Network Parameter Monitoring System is analyzed and the overall research scheme and design idea of the system are expounded. This paper mainly studies how to improve the accuracy of input voltage and current. The front-end voltage decreasing, current dropping circuit and remote data transmission circuit are designed. The programs of the data acquisition and calculation are made, real-time detection of power network parameters, energy calculation and the remote data transmission are achieved. Based on .Net platform, the host computer software is designed to receive the data and store them in the database, the mean value of power and energy parameters are calculated by the day, the week and the month, which are available to the user for inquiry. Many parameters such as three-phase voltage, three-phase current, frequency, active power, reactive power and voltage harmonics, can be detected by the system, which will provide a reliable basis for power quality analysis.

By analyzing the current situation of experimental platforms which is based on the Internet of Things (IOT) and the cultivation of talents, we established the talents' cultivating orientation and experiment platform for innovation. In accordance with the requirements of a students' practical and creative ability curriculum, the method of modularization was adopted to design this platform. With this, the platform can basically satisfy the needs of the varying teaching experiments, which can increase opportunities for the students on their comprehensive application. The platform was widely used in experimental and practice teaching in the past three years, such as synthetic experiment, graduate programs, and practice project in Zhongkai University of Agriculture and Engineering, Guilin University of Technology etc. Result shows that the innovation experimental platform has broad application prospects, and effectiveness to meet the requirements of students' in-depth learning and research of IOT technologies. Meanwhile, the platform expanded the students' basic understanding of IOT and improved their innovation.