Applied Mechanics and Materials Vols. 204-208

Abstract: At present, robot simulation based on virtual reality is a hot spot in the study of the robotic. We can build more intuitive and efficient and realistic simulation environment of processing of the robot through combining computer technology and virtual reality technology to carry out a more effective human-machine interactive operation. Robotic trajectory planning is not only the basis of trajectory tracking control, but also the implementation of tasks in robotics. It is discussed trajectory planning and path generation based on robot kinematics and dynamics in the joint space and Cartesian space. In this paper, we study the robot trajectory planning and use three B-spines fitting the robot path in Cartesian space.

Abstract: Estimation of Population covariance matrix from samples is important in a wide range of areas of statistical analysis. In the estimation, the sample covariance matrix, which is the most natural and standard estimator, often performs badly. With the collection of large high-dimensional data in scientific investigation, the related covariance matrix becomes complicated to deal with. Therefore, for the convenience in computing and analyzing, we need to simplify the covariance matrix. This method is referred as regularization. In this paper, we will consider a proof for a construction of covariance regularization by tapering.

Abstract: The method of computational fluid dynamics (CFD, Fluent code) was applied to simulate the Strouhal numbers of the empty and fulfilled U-shaped sections. Based on the N-S equation and k-ε turbulence model, the effects of Reynolds numbers and height/width ratios of the sections on the Strouhal numbers were investigated. The results of this study show that the Reynolds number has little influence on the Strouhal numbers, which decrease with the increase of height/width ratios of the sections. The conclusion of present study provides a foundation for the further study of vortex-induced vibration of U-shaped aqueduct bridges.

Abstract: This paper studies the parameter estimation for dual-rate Hammerstein systems. The finite input response model is used to approximate the dual-rate Hammerstein systems, and a recursive least squares algorithm is derived to estimate the parameters of the finite input response model. Based on the estimated parameters, the origin parameters of the dual-rate Hammerstein systems can be obtained. An example is provided to show the effectiveness of the proposed method.

Abstract: Gray level co-occurrence matrix (GLCM) is a second-order statistical measure of image grayscale which reflects the comprehensive information of image grayscale in the direction, local neighborhood and magnitude of changes. Firstly, we analyze and reveal the generation process of gray level co-occurrence matrix from horizontal, vertical and principal and secondary diagonal directions. Secondly, we use Brodatz texture images as samples, and analyze the relationship between non-zero elements of gray level co-occurrence matrix in changes of both direction and distances of each pixels pair by. Finally, we explain its function of the analysis process of texture. This paper can provided certain referential significance in the application of using gray level co-occurrence matrix at quality evaluation of texture image.

Abstract: This paper studies that the properties of case-weighted model when simultaneous omission of the ith row and the jth column of design matrix X. In other words, basing on case-weighted model, this article obtains the relation of total-data model and select-mean-shift outlier model about regression coefficient, leverage and potency.

Abstract: Gray level co-occurrence matrix (GLCM) is a second-order statistical measurement. In order to understand the characterization degree of GLCM’s different feature properties, we use images of Brodatz texture images as experimental samples, analyze the change process of feature properties in horizontal, vertical and principal and secondary diagonal directions under the situation of some elements’ dynamic changes such as distance of pixels pair, size of moving window and gray level quantization,. By analyzing the experimental results, this paper can provided certain referential significance in how to select feature properties reasonable in the application of image retrieval and classification and identification which are based on using GLCM as feature.

Abstract: Dynamic deformation data analysis and prediction is a complex systematic project. Aimed at the shortcoming of the traditional prediction model, a method to design the BP neural network based on Immune Genetic Algorithm(IGA) was proposed. The mechanisms of diversity maintaining and antibody density regulation exhibited in a biological immune system were introduced into IGA based on genetic algorithm. The proposed algorithm overcame the problems of GA on search efficiency, individual diversity and prematur, and enhanced the convergent performance effectively. The results show that the BP neural network designed by IGA have better performance in convergent speed and global convergence, and the forecasting accuracy is improved, which illustrates IGA-BP neural network has certain of value on dynamic deformation monitoring forecasting.

Abstract: A Ky Fan type matching theorem for weakly transfer compactly open valued mappings is established in FC-spaces. As applications, Fan–Browder type fixed point theorems and Ky Fan type coincidence theorems are obtained in FC-spaces.

Abstract: Numerical simulation method was used to study the problems on critical anchorage length of bolts. 3-D calculation model was built by FLAC program. By numerical simulation calculations, the conclusion could be drawn: the frictional resistance contribution had nothing to do with drawing forces, and was relevant to the bond stiffness of anchor mortar. And comparative analysis results of one engineering example showed that the calculated values by the presented method agreed well with the measured data.