Advanced Materials Research Vols. 433-440

Abstract: This paper presents a method of extracting and compressing required data from the DCM file for medical image geometric modeling. According to the characteristics of DICOM data, combining the idea of run-length coding with block coding, the rapid data compression and storage in RAM was realized finally. Compared with other coding methods, the encoding approach for DICOM data in this paper, not only saves the memory space and improves transmission efficiency, but also can read the required a single pixel, or part of pixel data from the compressed data conveniently.

Abstract: Aiming at the deficiency of the local minimum occurring in neural network used for speech recognition, the paper employs support vector machine (SVM) to recognize the speech signal with four different components. First, SVM is utilized to perform the speech recognition. Then, the results are compared with those obtained by the BP neural network method. The comparison shows that SVM effectively overcomes the local minimum existing in neural network and has the advantages of the accurate and fast classification, indicating that SVM looks feasible to recognize the speech signal.

Abstract: This paper study on the distributed real-time and embedded system middleware. Presents a comprehensive overview of the Data Distribution Service standard (DDS) and describes its benefits for developing Distributed System applications. DDS is a platform-independent standard released by the Object Management Group (OMG) for data-centric publish-subscribe systems. The standard is particularly designed for real-time systems that need to control timing and memory resources, have low latency and high robustness requirements. To illustrate the benefits of DDS for precision assembly an example application is presented.

Abstract: Radial weight and rotary torque load often demand large winding current in a bearingless switched reluctance motor (BSRM). This will tend to cause magnetic saturation. But traditional mathematic model can not fit for this saturated working state, which has formatted a sever limitation. With a BSRM model in Maxwell, its magnetic saturation characteristics were analyzed, and a critical criterion was computed. Then a novel mathematic model was established with Maxwell tensor method and confirmed by Finite element computing results. It could fit for both unsaturated and saturated working state, and also satisfy reversibility condition. These were both very useful for nonlinear decoupling with state feedback method and wide application in industry process. This proposed modeling and analyzing method could also provide useful references for motor’s optimization design and control algorithm research.

Abstract: High speed Ethernet traffic is important for some system tests which use TCP/IP as the data communication. A software way to do this job brings benefits on robust, but due to the limitation of CPU, it can not give full line speed of Ethernet frame, especially where short frame is needed. An implementation of an embedded high speed network traffic generator which is based on FPGA is introduced. It can be used to generate arbitrary length of PRBS Ethernet frame. Due to the high speed process ability of FPGA, even when the frame length is as short as 64 bytes, the speed is almost the full line speed as the theoretical value, which is 10 times fast than software method.

Abstract: This paper studies the mathematical model considering iron loss in the d-q axis of six phase permanent magnetic synchronous motor (PMSM), through the expansion of Field-Oriented Control (FOC) based on three phase PMSM, the simulation model of six phase PMSM under environment of simulink7.0 is set up, which has fast dynamic response, high steady-state precision, and has no problems about current balance compared to dual three phase PMSM. In order to get an accurate simulation results, this mathematical model takes iron loss into account. The simulation results show that iron loss have bad effects on the performance of PMSM especially affect the dynamic response, and to reduce the bad effects, the resistance of the motor core should be increased.

Abstract: versatile gate is a multipurpose device, which can be transformed into any types of gates, amplifier, differentiator, and integrator. It has control inputs which guides transformation of this device. This implies that any chip made of this device can change hardware structure just by using software program. This enables hardware upgrading without buying new chips. This reduces electronic wasteland, which proves that it is very ergonomic and environmental friendly.

Abstract: In this paper, considering some important indices such as closed-loop pole locations, speed of response and combining them into an objective function an optimization problem is defined in order to select the weighting matrices in Linear Quadratic Regulator (LQR) controller. To solve this optimization problem the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are utilized and compared. The proposed method is applied to rotational inverted pendulum. Simulation results show the relative superiority of PSO over GA.

Abstract: Metasearch engine is a system that provides unified access to multiple existing search engines. After the results returned from all used component search engines are collected, the metasearch system merges the results into a single ranked list which is expected to be better than the results of the best of the participating search systems. The success of a metasearch engine depends mainly on their rank aggregation method. The system is a better one, if the aggregated list of results displayed before the user satisfies the user with his information need. In this paper, we discuss the development of a metasearch engine that performs user feedback based metasearching using modified rough set based aggregation. Metasearching using the modified rough set based aggregation is performed in two phases namely the ranking rule learning phase and the rank aggregation phase. For each query in the training set, we mine the ranking rules and select the best rules-set by performing cross-validation test. Once the system is trained, we use the best rule set to get the overall ranking for the results returned from different search systems in response to other queries. We also present few snapshots of our system.

Abstract: A method for transmission gearbox fault diagnosis is put forward in this paper by using radial basis function neural network (RBF network). A RBF neural network is created to simulate the gearbox fault diagnosis using Matlab neural network toolbox. Compared with BP neural network, RBF network is superior to the former in accuracy and speed according to the simulate results. This method is accurate and credible in gear fault diagnosis, and it has a broad application prospect in mechanical fault diagnosis.