Applied Mechanics and Materials Vols. 313-314

Abstract: Network adapter is one of the most important components of NOC which is recommended to be used in present and future SOCs. In this paper, a network adapter compatible with OCP interface protocol is designed to enable the integration of IP cores from different providers into an on-chip interconnection network. In order to tradeoff communication performance with complication, the design of network adapter is based on a single global address space and supports burst transmission and virtual channel technology. With the goal of reducing transport latency, the processes of encapsulation and decapsulation are executing simultaneously with packet transmitting and receiving. Considering the simulation result, the network adapter presented in this paper gets satisfactory performance.

Abstract: First of all, this paper analyzes the calculation process of the load forecast of power system, and puts forward a new ideas of varieties of load forecasting method according to the classification on this basis, this paper will establish a global predictive function corresponding to different kinds of load forecasting methods, and designed the software on the load forecasting on the basis of such function. This paper describes the programming ideas of using the global predictive function to conduct the single forecast method and combined forecast, which demonstrates its advantages. Finally this paper has introduced the realization of global predictive function in Visual Basic language in programming, and the corresponding interface-building and use method. Actual use shows that, the use of global predictive function can significantly reduce the program size, add flexibility in the load forecasting software, which improves the scalability as well as the extensibility of the program.

Abstract: BP neural networks are widely used and the algorithms are various. This paper studies the advantages and disadvantages of improved algorithms of five typical BP networks, based on artificial neural network theories. First, the learning processes of improved algorithms of the five typical BP networks are elaborated on mathematically. Then a specific network is designed on the platform of MATLAB 7.0 to conduct approximation test for a given nonlinear function. At last, a comparison is made between the training speeds and memory consumption of the five BP networks. The simulation results indicate that for small scaled and medium scaled networks, LM optimization algorithm has the best approximation ability, followed by Quasi-Newton algorithm, conjugate gradient method, resilient BP algorithm, adaptive learning rate algorithm. Keywords: BP neural network; Improved algorithm; Function approximation; MATLAB

Abstract: Modern manufacturing system and processes are becoming increasingly complex, and requesting much function and tools to user. It also is operating in highly dynamic environments. Traditionally, flexible manufacturing system (FMS) was used. Nowadays, communication networks are available to virtually every aspect of the manufacturing environment. In the contents, manufacturing system with cloud computing is a good example. In this paper, we consider the cloud manufacturing system and their future works.

Abstract: Successful deployment of Wireless Sensor Network (WSN) depends on the availability of power sources. Conventional battery-based WSN components has several drawbacks, such as limited life-span, bulky size and hazardous to the environment. Hence, energy harvesting from ambient sources attracts enormous attention. But energy harvesting depends on the availability of the ambient sources. In most cases energy harvesting from a single source is not enough to produce sufficient energy to power up WSN components. This paper describe about the design, and implementation consideration of a hybrid energy harvester for an autonomous sensing system. The sensing components of WSN are connected with the hybrid energy harvester on the same structure to generate required energy from the ambient environment such as solar and chemical reaction. As a case study, the power requirements of in-house developed WSN components [1] are measured. Based on the power requirement a hybrid energy harvester based autonomous system is designed [2], and a functional prototype of the system is implemented. In the implemented prototype, energy is being harvested from the ambient solar and chemical sources. From the evaluation of the developed system, it is found that powering WSN components, hybrid energy harvester produces an additional amount of 10491.93 J (equivalent to 2.91 Wh) of energy, which is capable to fill-up a 971 mA-hr storage in one day operation. This is enough for the WSN components to draw power subsequently, when there is not enough ambient sources available for next few days.

Abstract: With the rapid development of the printing industry, the speed of the inkjet printer has soon become the focus. In view of the high requirements of printing speed, the in-depth analysis of the bottleneck, which restricts the press printing speed, is made. As the computer hard disk access data speed is limited at this stage, the high-speed inkjet printing system software based on distributed processing is developed. This software system based on object-oriented programming theory, by taking VS2008 as the development platform and using C/S system architecture, realizes multiple servers in parallel processing, data transfer and printing capabilities. The practical application proved that it deed improve the printing speed effectiveness and feasibility.

Abstract: As to the insufficient of difficulties to achieve sub-microsecond accuracy in full software implementation of LXI bus synchronization. Studies the LXI bus synchronization triggering and advances, the design program of FPGA-based hardware-assisted to achieve IEEE1588. Which lays a good foundation for the design and implementation of the Class A and Class B instruments.

Abstract: Proposed a new method establish the line fault monitoring system to achieve the real-time fault monitoring and location because so many power line open fault that caused by the cable theft or the frequent natural disasters such as ice storm and so on today, The system uses the power line carrier technology to locate the power line fault in one transformer area, and uses the Zigbee wireless communication technology to transmit the fault information within the jurisdiction of different transformers.

Abstract: Vehicle Type Recognition is the base and key point for Intelligent Transportation,Through the geomagnetic disturbance data of different vehicle type, constituting a sort of BP neural networks, and optimizing it using Genetic Algorithm. The result is good. This method can raise the recognition rate effectively and reduce the quantity of calculating. It has strong practicability.

Abstract: This paper presents a novel architecture of intelligent landing control of an airplane using dual fuzzy neural networks, including roll control, pitch control and altitude hold control. The neural network control has been implemented in MATLAB and the data for training have been taken from Flight Gear Simulator. The flight performance has been shown in the Flight Gear Simulator. The objective is to improve the performance of conventional landing, roll, pitch and altitude hold controllers. Simulated results show that control for different flight phases is successful and the neural network controllers provide the robustness to system parameter variation.