Earticle

There are a large amount of advantages to make efficient load phase balancing, such as loss minimization, energy restoration, security, reliability and voltage balance. Optimal load phase balance is obtained by solving the load re-distribution problem as a combinatorial optimization problem. This enables the best switching option that gives a balanced load arrangement among the phases and minimizes power loss to be arrived at. In this paper, adding decaying self-feedback continuous neural network (ADSCHNN) is applied to realize phase swapping for load re-arrangement in the low voltage circuit of the distribution network. The network energy function of the ADSCHNN is constructed for objective function that defines the load phase balancing problem. The ADSCHNN is applied to solve the problem when load is represented in terms of current flow at the connection points, and when load is defined in terms of the real power. The results obtained using ADSCHNN are compared with those from a heuristic algorithm, and from fuzzy logic expert system. Simulations results on real practical data show that the ADSCHNN is very effective and outperforms other known algorithms in terms of the maximum difference of the phase currents or powers.

Robot path planning is a NP problem, traditional optimization methods are not solve it very well just like genetic algorithm, which are easy to trap into local optimal. Particle Swarm Optimization (PSO) algorithm was developed under the inspiration of behavior laws of bird flocks, fish schools and human communities, compared with genetic algorithm the PSO algorithm has high convergence speed. In this paper, aim at the disadvantages of standard PSO algorithm like being trapped easily into a local optimal, we improves the standard PSO and proposes a new algorithm to solve the overcomes of the standard PSO. The new algorithm keeps not only the fast convergence speed characteristic of PSO, but effectively improves the capability of global searching as well. Compared with genetic algorithm on the robot path planning problem, the results show that the new algorithm can get more accuracy path and the calculation time is faster.

The improvement of system reliability can be achieved by improving the reliabilities of its constituent components. This could be done through maintenance actions that are performed on the components. There are two extreme states in which a component could assume following a maintenance stage; bad-as-old (BAO) or good-as-new (GAN). For some components of the system, the maintenance actions may bring them to an in-between state. This in-between state is achieved under the assumptions of imperfect maintenance. This paper investigates the improvement in reliability of a component and system in the in-between state through imperfect preventive maintenance policy. Thus, it establishes a mathematical model for component reliability evaluation under assumptions of imperfect preventive maintenance.

Sliding mode controller (SMC) is a highly significant nonlinear controller under condition of certain and partly uncertain dynamic parameters of system. This paper focused on design and implementation of a sliding mode controller for STATCOM. Intend for its application to wind farm connection to the grid. The proposed inverse system sliding mode controller based on nonlinear feedback linearization technology for system decoupling, which enhance the transient stability of wind farms and stabilizes the grid voltage about the given operating point when the fault occurs closer to the wind farms. The simulation results have shown the improved performance of the proposed controller has better control effectiveness and efficiency compared with the conventional controller of inverse system , the proposed controller on wind power system and which assist in improving capability of the wind farms to ride through disturbances, dynamic power flow control of the transmission lines, enhancing power oscillation damping under a sudden fault. Moreover, the proposed control scheme is very simple and easy to implement.

Wireless sensor networks are used in various applications in several domains for measuring and determining physical phenomena and natural events. Wireless sensor networks can support to observe characteristics of physical objects and features of natural incidents. This paper proposes a hierarchical architecture of semantic information for heterogeneous sensor data representation in the pig farm. This architecture provides various real-time sensing data such as pigs environment of piggery using temperature sensor, humidity sensor, wind speed sensor, etc. Information of this architecture supports to develop Sensor web for effective pig keeping in ecological pig farm environment.

In this paper, we present a vision based robust pose estimation system in different observed situations for a quadrotor in outdoor environments. This system could provide us with approximate ground truth of pose estimation for an outdoor quadrotor, while most of existing vision based systems perform indoors. We only use the own features of the quadrotor, while most existing systems modify the architecture of the quadrotor or put additional components such as colored markers on it. We propose the novel robust pose estimation algorithms for different observed situations. With good observed results, we get all of the four rotors and calculate the pose. But when fewer than four rotors are observed, all of existing external vision based systems for the quadrotor do not mention this and could not get right results. By combining inertial measurement unit (IMU) data, our robust pose estimation system has solved these problems and obtained accurate results of pose estimation. We demonstrate in real experiments that our pose estimation system for the quadrotor could perform accurately and robustly in real time.

This paper proposes a method for optimizing and parallelizing a pedestrian detection algorithm based on CENTRIST in the embedded environment. Pedestrian detection is applied to various areas, but there is a difficulty in the real-time processing of pedestrian detection in the embedded environment. In this paper, a pedestrian detection algorithm that has improved performance by reducing unnecessary memory access due to duplicate computations for real-time processing. The proposed algorithm was implemented in the ALDEBARAN embedded processor(300MHz) which can perform parallel processing. For efficient parallel processing, images were divided into halves which were then processed separately in two CPU cores and the volume of computations was balanced between the two CPU cores. For input images, 512x360 sized images were used. The single core showed the performance of 3.1 frames per second. In the dual core for which the wait time in the process of parallelizing was reduced, the performance improved by about 55% to 4.8 frames per second.

Because of high reliability and other characteristics, High Voltage Direct Current (HVDC) Light system had important applications in power transmission system. In order to ensure its operation safety, the fault diagnosis technologies based on observer were researched. The model of HVDC light system was introduced, and the types and characteristics of the system were analyzed. Several common fault diagnosis methods were discusses, including method based on analytical model, method based on expert system and method based on neural network. A fault diagnosis observer was designed, the output waveforms of observer were observed and analyzed when the failure occurred, the type of fault was determined, and finally, the automatic detection of fault in HVDC system was achieved. The test simulation results showed that this method detected the occurrence of failures, identified the faults in characteristics and provided evidence for exclusion and maintenance of fault.

This paper designs a tour recommendation scheme for electric vehicles and analyzes its performance. Aiming at reducing the time waste brought by long charging time, the recommender not just decides a visiting and charging schedule for the given set of user-selected tour spots but also integrate additional places, which have chargers and provide tour activities. Genetic operators, such as reproduction, selection, and mutation, are tailored to create a combinatory schedule of essential selected and optional recommended spots based on a hybrid orienteering model. Its encoding scheme represents a visiting order by a fixed-length integer-valued vector, allowing the omission of recommendable spots. In addition, the fitness function estimates time waste by tracing the battery charge state based on the inter-destination distance and stay time along a given route. The performance measurement result obtained from a prototype implementation discovers that our recommendation service can reduce the time waste by up to 12 % for the practical range of parameter setting, compared with the legacy tour scheduling method.

This paper considers supply chain models with two competitive manufacturers acting as the leaders and a retailer acting as follower under a fuzzy decision environment. The parameters of demand function and manufacturing cost are treated as fuzzy variables. Two manufacturers are assumed to pursue Cournot competitive behavior and the optimum policy of the expected value and chance-constrained programming models are derived. Finally, a numerical example is provided to illustrate the results of proposed models. It is shown that in fuzzy models, the confidence level of the profits for supply chain members affects the final optimal solutions.

This paper presents a novel current differential protection scheme for UHV/EHV transmis-sion lines. This method is based on active current component extraction using instantaneous power theory, which is also called ip-iq method, and it has been widely used in APF (active power filter). Adopt three digital PLL (phase-locked loop) to get the positive voltage’s angle and active current containing DC and AC components can be obtained by using dq transfor-mation. The average filter is employed to filter the AC active current component out. This algorithm can eliminate the influence of distributed capacity current fundamentally. Com-pared to compensation methods, it requires no heavy computation, line parameters and volt-age information transmission. Compared to other differential protection methods, it has the advantages of clear physical meaning and simple operation. Simulation results show that the novel protection method is effective and robust, providing a new perspective on transmission lines’ protection.

This study examines conductive noise in long distance cables in a subsea environment. The inverters currently used in subsea plants generate conducted noise, which is the cause of damage and insulation failure of electric motor bearings. In particular, it is important to analyze the characteristics of transient voltages for different subsea temperature and pressure changes. To analyze the transient voltages, the effects of L, R, and C for different temperature and pressure changes were investigated. Among the analysis factors of L, R, and C, the capacitance C was identified as the factor that influences conductive noise the most. As a result, we analyzed the impact of the electrical components (L, R, and C) on the noise in the design stage of a long-distance cable, focusing on the variables of pressure, and presented the guidelines for designing a subsea plant model.

In order to adapt to the development of the mobile Internet, intelligent small mobile terminal will be the future trend of development. This paper describes the implementation of data communication between the Android operating system and PC. Besides, this paper also presents some solutions of key issues, including the event processing of mouse movement area involved in Android mobile client, the event processing of command button and mouse movement involved in PC server, etc. To meet the needs of schools and educational institutions, an Android wireless mouse and keyboard software based on C / S mode is developed, hoping to replace similar electronic pointer and achieve long-range wireless control.

It is an essential factor in automatic navigation systems of ground vehicles, railroad and aviation fields which require high stability to detect the global position of vehicles with credibility and accuracy. This paper proposes an approach to estimate the global position of vehicles moving in the predefined path with a set pattern. Because the information of location received by GPS is included various errors, the errors are minimized using GPS error filter and map matching to obtain correct information. The velocity profile is one of key information for the system model of moving vehicles. We propose an estimation scheme using adaptive Kalman filter where the system model is derived from the moving pattern of vehicles. Since there is high probability that the position obtained from the adaptive Kalman filter is deviated from actual road and/or railway path, we remove the error by using map matching technique. The proposed scheme was experimented in position detection of train moving along predefined section of railway.

The analysis of electric field distribution in electrospinning machine is critical to the nanofiber preparation. In this paper, electric field strength is calculated based on finite element calculation theory of electric field. Electric field structure of plate-plate type electrospinning machine is simulated using ANSYS software. And vector distribution of nozzle on spinneret pipe of plate-plate type electrospinning machine is obtained. The simulation analysis provides an effective reference for the electric field’s distribution of the plate-plate type electrospinning machine. Based on the experimental system of the plate-plate type electrospinning machine, electrospinning experiment with different spinning distance and extrusion speed is performed. The experimentation results show that fiber diameter decreases with the increase of spinning distance, and the extrusion speed and the diameter of the fiber conform to the direct proportion.

As the grid voltage of the V/v power supply system for high-speed railway is distorted, the detection method for harmonic and negative sequence current is complex, and there are errors in the detection result. A method is proposed in order to solve these issues, which is capable of carrying out fast and accurately comprehensive compensation for grid current without the PLL circuit. During the detection process, a group of sine and cosine function with arbitrary initial phase angle is needed, the grid fundamental positive sequence voltage is extracted to participate into the detection of fundamental active power component to obtain the command signal. The calculation process is fast and simple and not affected by the distorted grid voltage. The correctness and feasibility of this method is verified by the result of simulation

This paper presents investigations into the development of a Proportional-Integral Sliding Mode Control (PI-SMC) for trajectory tracking and vibration control of a flexible single link manipulator. The motor at the single rotating joint is the control actuator. Two SMC control laws are reviewed. The classical discontinuous control based on the signum function and a modified control law where the servomotor output voltage depends on the instantaneous values of the states. The selection of the discontinuity gain is reviewed for exact model (certain case) as well as when the parameter variations are present (uncertain case). To prove the reaching condition, we use the Lyapunov stability criteria. It is proven that this design is equivalent to a full state feedback with its steady state motion constrained to the sliding hyper-surfaces. Simulation results of the response of the flexible manipulator with both controllers are presented. The performances of the control schemes are examined for input tracking capability, level of vibration reduction and time response specifications. A comparative assessment of both control techniques shows the effectiveness of the second control law and its invariance to so-called matched uncertainty.

Network traffic is a typical time-series data with strong lag and aftereffect, for the existence of local optimum, time-consuming and other defects in the method for the currently determining number of lags, this paper presents a combination of network traffic prediction method (GS-GA-LSSVM). At first, using geo-statistics (GS) to quickly determine the optimal lag order of network traffic, then reconstructing network traffic with the lag order, and finally using genetic algorithm (GA) to optimize least squares supporting vector machine (LSSVM) to model predictions for network traffic. Simulation results show that, GS-GA-LSSVM on network traffic prediction accuracy is better than any of the participating models, and which can better reflect the complex dynamics of network traffic disciplines.

Knowledge of flow distributions from a stream of packets passing through a network link helps a network operator infer traffic demands, characterize source traffic, and detect traffic anomalies. Flow monitoring provides critical information for many network applications, and some approaches have been proposed to address flow monitoring. However, they either lack accuracy, or require intensive computing resources. In this paper, we propose a Resource-Efficient System (called RES) for monitoring flow distribution, which consists of Double sampling module, Online streaming module, and Offline processing module. Using real network traffic traces, we show that the RES indeed produces the desired accuracy in monitoring flow distribution.

The Exhaust-Gas Recirculation (EGR) is the effective method to reduce the exhausted NOx from diesel engine. The EGR system needs to be cooled to lower the combustion temperature, which results in the reduced engine power. To improve the performance of EGR Cooler, maximizing heat transfer coefficient, heat transfer area and corrosion resistant material should be considered while the thermal stress produced by the temperature difference between exhaust gas and coolant is also considered as a highly important factor from the point of safety operation. The thermo-flow characteristics inside the EGR Cooler and surface temperature have been investigated by using CFD code STAR-CCM+ 9.0. Finally, as a result of the simulation, the stress location and crack spots has been experimentally observed and compared with simulation. The focus is going to be mainly on CFD simulation and flow behavior inside the EGR which is considered important in order to improve the efficiency.

A new sorting control system in field programmable gate array (FPGA) — the core of control — was proposed because the previous one couldn’t meet the requirements of the multi-channel and high yield. It focused on designs of both hardware circuit and FPGA programming module. In the system, the accurate lossless delay of multiple signals was applied by using of RAM and its control module in FPGA. The sorting signals were generated based on the parallel execution characteristics of FPGA program. Real-time communication was realized between CAN controller of SPI and human-computer interface. A large number of experiments were done to test the proposed system. Results showed that the sorting control system could process multi-channel and higher-yield signals significantly. And the materials sorter was improved both in detectable level and yield.

Wind power prediction has become a hotspot in recent years. The parameters relevant to the wind power are considerable and complexity. Dimension reduction has become another hotspot. The traditional methods utilize linear methods to reduce the dimension of measured data. However, data that located in high-dimensional space often have nonlinear structure. So, we consider the original data present manifold structures and introduce manifold learning methods to extract the important information. In this paper, we utilize LLE algorithm and Elman neural network to establish the wind power prediction model. The experiment results demonstrate the excellence of our method. Finally, we chose different algorithm parameters to complete the experiments and got the roughly optimal parameters. In addition, our method can be applied to similar fields.

This paper proposes a method to optimize a supply chain network for yacht service that maximizes values for service users / customers, and profits for service providers. The yacht industry includes many sectors such as yacht design, yacht engineering, yacht manufacture, marina service, yacht maintenance, finance/insurance, training and education for professional and non-professional sailors, chartering, leisure service, and technical clothing. In order to boost up yacht / marine leisure culture, we must consider yacht infrastructure, yacht research, and yacht service from a systematical point of view. This paper uses the C2C cycle to optimize a yacht service supply chain network inclusive of design, research, manufacture, and leisure service.

This paper presents a motion planning method for archwire bending robot in orthodontic treatments. Because the movement of the archwire bending robot belongs to typical hybrid point-to-point movement, which has both long and short distance, thus the traditional acceleration/deceleration (acc/dec) method is not suitable for this mode of motion. In order to improve the stability and relief the impact and vibration in the process of archwire bending, a new motion planning method that based on three-order pure S acc/dec curve, 5 segments acc/dec curve, and modified acc/dec curve is established and a piecewise self-adjustment acc/dec strategy that based on displacements of three-order pure S acc/dec curve, 5 segments acc/dec curve, and modified acc/dec curve is proposed. The effect of acc/dec methods on the process of archwire bending is analyzed, and verification of the proposed method is conducted through MATLAB simulation. The MATLAB simulation realized validity of the motion planning.

Owing to all the advantages of angular contact ball bearings (ACBB), including little energy consumption and low friction, etc, ACBB becomes the prior options for supportive components of NC machine tool spindle units. Thermal and mechanical behaviors of rigid-preloaded-ACBB are highly coupled, which produces the thermal preload. For investigating the effects of thermal preload on the bearing performances, this paper presents an ACBB thermo-mechanical information interaction net which is constructed on a collaborative computing platform. During the case study process, the thermo-mechanical information interaction net of a NSK ACBB 70BNR10X is realized. Thermal preload of the given ACBB is then predicted and analyzed through the information interaction net. In addition, effects of thermal preload on the ACBB operational stiffness are studied. With the help of temperature inspecting instrument, temperature tests are provided on the bearing thermo-mechanics test platform to validate the interaction net. Great agreements are found between the results predicted by the interaction net and the datum obtained through experimentation. The proposed information interaction net is useful for investigating the behaviors of running-bearing.

The evaluation standards of management efficiency for managing the water supply can be called the Revenue Water Ratio. The revenue water ratio is an important index that shows the standards on the cost of production as well as the ratio of quantities received through the rate income from the total amount of water supply produced from the water treatment plant. In general, the calculation of revenue water ratio is made on the basis of small blocks after the progression of blocking business, thus the management of water pipe network is also made on the basis of small block unit. However, the boundaries of adjacent blocks have many obscure points with many number of blocks, there are many difficulties of performing the work by the limited management personnel. Therefore in this paper, in order to improve the problems and limits of the previous block monitoring system based on inefficient small blocks, a block monitoring system based on real-time flow analysis centering on the middle block is proposed. In addition, by performing the dynamic pattern-based abnormal flow analysis considering the characteristics of each block and also by performing the real-time analysis on the rate of water supply between the classes, it will prove that the efficiency of management can be improved.

Image Segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Pre-processing of the image makes it more clear and visible, while parallelizing of the algorithm optimizes the speed at which the image is processed. This paper presents the performance analysis of parallelizing the video frame segmentation using region growing technique on varying of processors. Region growing Technique is also classified as pixel-based image segmentation method since it involves the selection of initial seed points where determining of whether the pixel neighbors should be added to the region or not is done. The process is iteratively carried out and the region is correspondingly grown for each image. Video is divided into frames, which are passed to different cores. The processing of frames is carried out simultaneously in cores, hence parallelizing the technique. Time analysis for serial and parallel implementation is done. Analysis of time required for processing the frames on different number of cores is carried out.

Dispatching automation system is the nerve center of power grid. When using the system, it usually needs grid model diagrams, such as plant station wiring diagram, flow calculation diagram, etc. In addition, the model files are used for grid monitor, dispatching analysis, etc. Thence before use, these files need to be approved strictly for ensuring the security of the running power grid system. This paper briefly describes the dispatching automation master system iES600Pro of Integrated Electronic Systems Lab Co. Ltd. (iESLab). Moreover, it proposes a system optimization scheme based on workflow technology, thus the system can implement complete approval process of model files. The process is flexible, convenient and customizable. Furthermore, it presents the implementation of scheme including the architecture of system after the optimization, the description of interfaces between system components, the design of business data table, a sample of approval process, and finally the testing platform and results. The results show that the proposed scheme improves the system function and approval efficiency. It is more conducive to the security of grid dispatching.

The damages caused by natural disaster are unpredictable. It is almost out of control because its scale is entirely different from what we have experienced before. Natural disaster of climatic change is getting force. The effects of the disaster like flood block the energy supply route which is the municipal Lifeline. This is very dangerous and causes states of emergency. The blackout occurred in September 2011 showed that it causes extensive damage to the whole society. Especially important facilities like hospitals even suffer worse situations which cause casualty. This study examined, through field investigation, the actual conditions of large general hospitals’ energy consumption and the status on their establishment of emergency power systems. Based on such investigation, analysis was made of the ways to establish emergency power systems capable of maintaining properly the functioning of hospital buildings and providing effective response during massive blackout.