Data Interface Module Research Articles

High‐speed distance relaying using least error squares method and testing with FPGA

The demand for high-speed protective relaying in modern power grids is growing. A relay's fast and secure operation to clear faults is critical, especially for EHV/UHV transmission systems (400 kV and above). This research proposes a sub-cycle distance relaying, which is based on the least error squares (LES) method, and with a data interface module implemented on field programmable gate array (FPGA). Taking advantage of inherent parallelism and pipelined architecture of the FPGA, the proposed relay design can support real-time data communications. Also, the flexible and reliable feature of the LES algorithm allows the proposed relay to make a fast and secure trip decision in different scenarios. The case studies demonstrate the effectiveness of the LES-based relay.

A Simulation Method for LIDAR of Autonomous Cars

Vehicle-mounted LIDAR simulation module is an important part of autonomous car simulation test platform. According to the working principle of LIDAR, its working process and interface can be simulated in the digital simulation environment. The environment includes LIDAR emulation module, high precision 3D scene model and data interface module. The LIDAR simulation module uses GPU(Graphic Processing Unit)to calculate the depth of high-precision 3D scene and output the results through data interface. On the PC workstation, 64 lines vehicle-mounted LIDAR can be implemented for real-time simulation of large-scale road scene.

The Analysis of Node Planning and Control Logic Optimization of 5G Wireless Networks Under Deep Mapping Learning Algorithms

In order to meet the needs of blowout growth of data flow and 10-100 times increase of user experience rate, the next generation mobile communication(5G) heterogeneous network deployment will use ultra-dense network. Accurate fault location is the basis of slice management. In virtualized network model, the function of network elements is software, the underlying layer is highly abstract, the structure changes dynamically, and common cause faults occur frequently, which brings difficulties to fault location. Deep Learning is a machine Learning method that USES Deep Neural Network (DNN) with multiple hidden layers to complete Learning tasks. The essence is that by building a neural network model with multiple hidden layers and using a large amount of training data to learn more useful features, the accuracy of model prediction or classification can be improved. Based on the theory of deep mapping learning algorithm, a scheduling algorithm based on event-driven access point, improved time-driven access point and idle network is designed for centralized wireless network control system. Aiming at the centralized wireless network control system, this paper designs a scheduling algorithm based on event-driven access point, improved time-driven access point and network idleness. The designed sensor network node platform uses the programmable logic controller as the main control chip, contains the data interface module that realizes the communication function between the node and the upper computer, and the acquisition and conditioning module responsible for the collection and conditioning and conversion of the analog signal. At the same time, the TCP and UDP are compared and studied. The accuracy of the model is verified, and the interference distribution of the model and the influence of the D2D inter-pair distance on the system performance are simulated. The distance between the D2D pairs under the given simulation parameters has a certain influence on the system performance. As the distance increases, the system performance will deteriorate, but the impact is not a big conclusion.

Production Planning System for the Whole Steelmaking Process of Panzhihua Iron and Steel Corporation

A production planning system is designed for the whole steelmaking process, which includes desulfurization, vanadium extraction, steelmaking and continuous casting processes of Panzhihua Iron and Steel Corporation. The system is composed of modeling module, data interface module, data analysis module, static planning module, re-planning module, plan evaluation module, plan simulation module and human-computer interaction module. The system is connected with the L3 system of steel plant by using the data interface module, which can receive the real time scheduling information to make the static plan and re-plan under production disturbances. The simulation and plan evaluation function of the system can assist decision-maker to check and modify the production plan. The simulation experiments with real process data show that the system can make a feasible, executable, and effective production plan, and deal with primary random disturbances during production process timely.

Mobile Physiological Measurement Platform With Cloud and Analysis Functions Implemented via IPSO

A physiological measurement platform is proposed for enabling users to measure physical condition regularly and to maintain good physical condition. The proposed system combines three basic physiological signal acquisition modules: an ECG module, a blood pressure module, and an oxygen saturation module. The physiological signals captured by the three physiological signal acquisition modules are sent via a data interface module to a mobile handheld device. Three communication systems are used for data transmission: RS-232 serial port wired transmission wireless, ZigBee, and Bluetooth. The captured physiological signals are presented on Android system mobile handheld devices, and the physiological data received by the mobile handheld device are sent to the cloud server via the Internet. After establishing a personal physiological database in the cloud server, the improved particle swarm optimization algorithm is used to determine the best personal physiological data, while setting physiological data dangerous levels for preliminary diagnosis. The dangerous levels are adjusted and set according to the personal medical records and physiological data of the subjects. When the physiological data reach the designated danger levels, it gives a warning to seek timely treatment by a medical unit. Finally, the system can incorporate video equipment to enable remote diagnosis and consultation by medical units.

The Research on Modeling and Dynamic Simulation of Gear Box Virtual Prototype Based on Pro/E and ADAMS

In this paper, the combination of Pro\/E and ADAMS to build a virtual prototype model of gear transmission, the dynamic simulation of the gear meshing process, study on dynamic speed, mesh force bearing load, where, for the gear box of the engineering analysis and optimization design. A 3D modeling and designing software, established a parametric model of a gear box of the rack and pinion drive mechanism, which is used in large gantry milling machine XK2425-600. The data interface module MECHANISM/Pro is used to convert the Pro/E model data to ADAMS, and then the virtual prototype is built in it. The rotational speeds, meshing forces, and reactive loads at bearings are obtained by dynamic simulation of the virtual prototype, which can be used in finite element analysis as boundary condition, helped to calculate the strength and stiffness of the box.