Papers by Author: Yu Hong Du

Abstract: A classification processing method of cotton foreign fibers was proposed based on probability statistics and BP neural network. Due to the origin was wide, the type was complex and the characteristic of cotton foreign fibers was different, it was difficult to build a model on classification and identification of cotton foreign fibers in the detection process of cotton spinning enterprises. This method could solve this question elegantly. Firstly, obtained the sample data by extracting the mean value of R, G, B in the fiber image and built a model about BP neural network. Then, classified 2-types cotton foreign fibers by calculating absolute value and variance of the feature vector based on probability statistics. Finally, processed the extraction features according to the different types image. The cross-validation experiment, the results show that the method combining the probability statistics and BP neural network can classify the cotton foreign fibers efficiently, and the effect is better when the types of cotton foreign fibers corresponding to the different features extraction methods The cross validation experiment, results showed that the combination can effectively identify the classification of foreign fibers and BP network based on probability and statistics, and different types of contton foreign fiber used different feature extraction methods, the effect is remarkable.

Abstract: As a good experimental platform for multi-agent system, Robot Soccer World Cup (RoboCup) has become a hot topic of artificial intelligence. This paper reviewed the technical characteristics of related robots in Simulation, Small Size, Middle Size and Humanoid It introduced the intelligent control algorithms such as Agent structure, Kalman filtering, self-positioning of robots and ZMP stability judgment.

Abstract: The value range of the cylinder wire front angle of cotton combing frame determines the effect of cylinder combing, with the analysis of the force of fiber in comber cylinder wire, a mechanics model is established. Combining with the test verification, we can get the calculation model of the cylinder wire front angle of cotton combing frame. The model indicated that the value range of the cylinder wire front angle of cotton combing frame is decided by the varieties of cotton fiber and parameters of combing machine process, thus this paper provides reference for the development of the cylinder wire of cotton combing frame.

Abstract: The constitution and structure of positioning system of gantry robot for dyestuff liquid proportioning with its synchronous belt driven flexibly is introduced first. According to the law of power balance, the method for coefficient pairing comparison is adopted to establish the kinetic model with the titration head in direction y and the modal analysis is carried out for kinetic coupling of the synchronous belt positioning system as well as the harmonic excitation vibration and response cause by polygonal effect of the synchronous belt.

Abstract: The basic equation of axial flow pump is derived from the assumption， which axial plane velocity and circumferential velocity distribute linearly along the blade radius. Based on the basic equation, the axial plane velocity and circumferential velocity gradient of discharge blade are calculated, and the flow field of pump is built. Using arc method of design blade, a design case is given. The standard K- epsilon turbulence model is applied to simulate the flow field of axial flow pump by FLUENT software. The simulation results indicate that pump efficiency reach 91%, there aren’t impact or vortex in pump, and the pressure distribution on the blade suction surface is even and high, the anti-cavitation performance is improved.

Abstract: Stability of cotton flow velocity determines the accuracy of foreign fiber detection system. There are many factors affecting fiber flow flux. In the process of operational control, recent research has been directed towards synthetically and effectively adjusting the relative parameters, and thus achieving a stable and economic foreign fiber detection system in textile sector. In the foreign fiber detection system, the parameters of flow velocity are affected by the temperature, pressure, density, which are also interrelated and redundant information. Based on Clustering Fusion, the design of the flow velocity used in the detection device is provided in this paper. Using captured parameter characteristic information, clustering fusion control, conducts the second fusion for ART-2 and BP neural network, and sends to fusion center, then fusion center process the data using neural network method. Linking with synthesis repository and global data base, different control strategies can be utilized to adjust velocity of flow parameter. The cluster control strategy that keeps output velocity of flow stable are proposed to improve the fiber measure precision in foreign fiber detection system. This system can be used in indigenous foreign fiber detection system, and significantly improve the performance of the entire system.