Applied Mechanics and Materials Vols. 448-453

Abstract: Cloing and hypermutation of immune theory were used in optimization on particle swarm optimization (PSO), an immune particle swarm optimization (IPSO) algorithm was proposed , which overcome the problem of premature convergence on PSO. IPSO was used in BP Neural Network training to overcome slow convergence speed and easily getting into local dinky value of gradient descent algorithm. BP Neural Network trained by IPSO was used to fault diagnosis of power transformer, it has high accuracy after experimental verification and to meet the power transformer diagnosis engineering requirements.

Abstract: In this paper, a Direct Method-based delay-dependent stability criterion is presented. Initially, the Lyapunov-Krasovskii functional of power system with double time delays is simplified, then the derivative of Lyapunov-Krasovskii functional along time is converted into the pattern of linear matrix inequality (abbreviated as LMI). During the process of derivative construction, an integral inequality is introduced to magnify the derivative, thus no free-weighting matrix is utilized in the new criterion. It can be proved that the new criterion, in comparison with the former ones with free-weighting matrix, has the same conservativeness and much fewer unknown variables. Finally, the proposed criterions effectiveness is validated by the typical second-order delay system and WSCC-3-generator-9-bus system. Numerical results indicate that the proposed criterion can obtain the same stability margin with the former ones with free-weighting matrix, but the improved criterion can remarkably curtail the calculation time.

Abstract: Content-Based Image Retrieval (CBIR) system existed a gap between high-level concepts and low-level features. As an effective solution, the Relevance Feedback (RF) technique has been used on many CBIR systems to improve the retrieval precision. In order to further improve convergence speed and retrieval accuracy, a novel relevance feedback method was proposed. According to feedback from user, image feature was weighted and adjusted in the novel method.

Abstract: Image fusion method based on the non multi-scale take the original image as object of study, using various fusion rule of image fusion to fuse images, but not decomposition or transform to original images. So, it can also be called simple multi sensor image fusion methods. Its advantages are low computational complexity and simple principle. Image fusion method based on the non multi-scale is currently the most widely used image fusion methods. The basic principle of fuse method is directly to select large gray, small gray and weighted average among pixel on the source image, to fuse into a new image. Simple pixel level image fusion method mainly includes the pixel gray value being average or weighted average, pixel gray value being selected large and pixel gray value being selected small, etc. Basic principle of fusion process was introduced in detail in this paper, and pixel level fusion algorithm at present was summed up. Simulation results on fusion are presented to illustrate the proposed fusion scheme. In practice, fusion algorithm was selected according to imaging characteristics being retained.

Abstract: Image fusion method based on image multi-scale decomposition is a kind of fusion method of multi-scale, multi-resolution image fusion. Its fusion process realize in different scales and different spatial resolution and different decomposition layer. Fusion effects based on multi-scale decomposition algorithm can obviously improve compared to the simple fusion methods. Among the fusion algorithm based on multi-scale to pixel-level image fusion, Pyramid decomposition and wavelet decomposition are widely used, the original image is decomposed to convert the original image domain to transform domain, and then, fusion process realized in transform domain according to certain rules of image fusion. Basic principle of fusion process was introduced in detail in this paper, and pixel level fusion algorithm at present was summed up. Simulation results on fusion are presented to illustrate the proposed fusion scheme. In practice, fusion algorithm was selected according to imaging characteristics being retained.

Abstract: Technology Readiness Levels have a great superiority to evaluate new technologies, and have been adopted by U.S. Congress General Accountability Office, Department of Defense and will be considered in numerous other organizations. In this study, Technology Readiness Levels are customized to assess the Digital Instrumentation and Control system of nuclear power plants. The Technology Readiness Levels evaluation system based on Browser/Server structure is designed. The flow chart of the evaluation system, automatic data analysis system, and the tables relation of database are presented. The Browser/Server structure enables multi-experts use Browser to assess the Digital Instrumentation and Control system of nuclear power plants in different places through the Internet. The Technology Readiness Levels evaluation system can easy the organizing work and reduce fees of Technology Readiness assessment works of Digital Instrumentation and Control system.

Abstract: We concern with the classification problem of generalized linear control systems, which might be useful for some engineering applications. Inspired by the work of Shayman and Zhou in 1987, we give the definition of linear, differentiable and topological equivalence for a special class of generalized linear systems in a unified way. Then we derive some properties on these three kinds of equivalences and show the canonical forms through a concrete example. In this paper, we obtain natural generalizationsof the Brunovsky's feedback equivalence theorem and the Willems' topological classification theorem for usual linear control systems.

Abstract: A weighing instrument system embedded multifunctional intelligent has been developped, and a compensation method proposed to improve the measurement accuracy of the system performance. Weighing instrument took embedded computer as the core, used the logic processing of the powerful FPGA, USB interface data communication function connecting to the PC machine to build host/slave system. Dynamically compensate in the series compensation link to solve the system of nonlinear strength, poor dynamic performance of sensor, short the time to reach the steady state for the whole measurement system. Results show that the system is suitable for the requirement of fast measurement, effectively improve the accuracy and reliability.

Abstract: Traditional pattern classification methods are not always efficient because sample data sets are sometimes incomplete and there are exceptions and counter examples. In this paper, SOFM neural network is applied in pattern classification of two-dimensional vectors after analysis of its structure and algorithm. The method to establish SOFM network via MATLAB7.0 is introduced before the network is applied to classify two-dimensional vectors. The adjustment process of weight vectors together with classification performance of SOFM model are also tested in the condition of different number of training steps. The simulation results show that the classification approach based on SOFM model is effective because of its fast speed, high accuracy and strong generalization ability.

Abstract: Network bandwidth can effectively support learning content such as multimedia files under, and intelligent terminal equipment for mobile clients humanization and functional design. Therefore, through the rational design of mobile learning platform that can effectively complement traditional learning less flexible. This paper study the direct MYSQL command in the terminal to use SQL statements to the database building a database, insert the initial exam and so on. In the latter part of the maintenance process, while using the first method and the third method updates the database maintenance work.