Abstract: A bionic chewing robot was designed to measure the mechanical properties of food, and the measuring mechanical properties of food include hardness, viscosity, elastic and chewiness. The bionic robot was composed of six mechanisms, each mechanism include there kinematic pairs, namely, revolute joint, sphere joint, sphere joint. This paper introduces the chewing robot mechanism aim to simulate the function of mandible of real mankind, and established the equation of reverse kinemics of chewing robot according to the structure of the chewing robot. Through the simulation module of NX, the equation of reverse kinemics of chewing robot was simulated.
Abstract: In the vector control the time constant of rotor changes will affect the system, generally required online identification. This paper puts forward a identification method based on model reference adaptive, using popov exceed stable to design a adaptive rate. Analyses identification system by torque effects, and proposes a kind of compensation algorithm, to improve the system robustness. Under the MATLAB/Simulink environment build simulation model to verify the correctness of the algorithm, and points out the advantages of compensation algorithm.
Abstract: We propose a real-time prediction method based on PCA and improved multi-step Elman net. The method not only preserves most original data information, but also eliminates the relativity among data and simplifies the net structure. It can predict the complex and nonlinear systems with dynamic recurrent algorithm. Through training the net has the ability of adapting to the uncertainty of the nonlinear structure, and then reflects the dynamic character of the systems. The hit rate reaches 88.17% to forecast the silicon content in hot metal of a blast furnace with errors ranging from-0.05 percent to 0.05 percent. The results prove that this method is feasible to predict silicon content on blast furnace and also it’s a prediction method of nice future.
Abstract: Large aperture collimator which has been widely used for calibrating and testing various optical devices plays an essential role in correlative laboratories. As being the basic testing and calibration equipment, the large aperture collimator’s accuracy should be much higher than the device under testing in order to ensure the accuracy of the measurement. However, the process of adjusting the collimator is extremely complicated due to the collimator’s large aperture and long focal length. So it is difficult to ensure the measurement’s quality and easy to cause the system being vulnerable to the surrounding environment. One of the most common problems is defocus. In order to solve the problem above, this issue presents a new type of autocollimator autofocusing system which uses pentaprism instead of using large-aperture plane mirror, semiconductor lasers as light source and CCD sensor as receiver. The system is smaller, lighter, and more convenient when using. The computer simulation shows that the autofocusing system’s resolution could reach the accuracy of 40μm. If we use the relevant algorithms to execute the sub-pixel scanning, the resolution could reach the accuracy of 10μm. It shows that the system could satisfy the required testing precision of testing large aperture optical device.
Abstract: Compressed Sensing (Compressed Sensing, referred to as CS) is a new theory of data acquisition technology. On sparse or compressible signals, it can capture and represent the compressible signal at a rate significantly below Nyquist rate and adopt non-adaptive linear projection to keep the information and structure of original signal, and then reconstructs the original signal accurately by solving the optimizational problem. Compressed sensing breaks the bottleneck of the Shannon Theorem because it cuts down the costs of saving and transmission in data transfer. This paper briefly describes theoretical framework and the key technology of the CS theory, focuses on introducing the application in reconstructing image information of CS theory and then makes a simulation using matlab. As expected, the simulation results show that CS can reconstruct the original signal accurately under certain conditions.
Abstract: By introducing ES (Expert System) of AI (Artificial Intelligence) and KP (Knowledge Processing), etc. into DSS (Decision Support system), the study on design of IDSS_EER (Intelligent Decision Support System of Engineering Equipment Repair) is discussed in detail combined with the characteristics of EER (Engineering Equipment Repair).To start with, the research status quo and analysis of IDSS problems are analyzed and the traditional design problem of IDSS is improved in the system structure and system function of IDSS with a clear aim. Finally, the design and development of IDSS_EER are given a particular description. The system design embodies the strong points of the qualitative and quantitative analyses and can be achieved theatrically and technically. Simultaneously, the system provides the man-in-the-loop support and avoids the intelligent blindness.
Abstract: According to the current actual situation of informatization in Commercial Vehicle Company of DF Motor Co., Ltd. , there exists such a problem as the incomplete parts data of S-BOM, which fails to provide complete parts data of the department of procurement and sales. In order to solve the problem, this paper designs and develops the parts of DF Motor Co., Ltd. Data Management System. The system uses Delphi 7.0 as the development tools and Oracle 9i as the back-end database，which implements the function of centralized management, maintenance and query of S-BOM parts data by means of parts state management, structured data management, parts data query and other function modules. The system meets Commercial Vehicle Company's requirements of centralized procurement by addressing some of the key issues in the original parts management. Fund Project: Key Projects of Science and Technology Research of Hubei Department of Education (No. D200723003 ); Projects of National Natural Science Foundation, 2010(No. 51006132)
Abstract: In this paper, a newly design of pulse-wave data collection system continuously and non-invasion by using the means of clip-on transmission oxygen sensor for getting information of pulse-wave, using the wave can calculate a number of important parameters of blood, it may solve the problem of real-time, continuous and dynamic blood flow monitoring in clinic, This design use sensor to get photoelectric volume pulse wave then the signal through amplification and filter circuit ,after then it is sent to A / D converter and DSP. The powerful instruction functions and fast processing speed DSP makes this design can quickly and easily detect the pulse wave signal. This design not only used for clinical care, but also can be used for community or family health care on detection of cardiovascular blood flow. This design can make the telemedicine care ture by DSP and the PC communication, It provides a simple and easy method to monitor the pulse-wave signal .
Abstract: Based on the foundation of prediction of networks security situation models, this article proposed a method about applying wavelet kernel function network to prediction of networks security situation. Wavelet kernel function network combined with the neural network and the support vector machines merits, which avoid support vector machine (SVM) solving binding second convex programming problem, network scale doesn't happen dimension disasters problem because kernel function is introduced, and its solution is the global optimal solution, so the situation prediction is more accurate. The experiment tests indicated that this method can accurately acquire the situation value prediction results, it has the good situation prediction potency, which provided one new key for prediction of networks security situation.