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Dive into the research topics where Zhenghe Song is active.

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Featured researches published by Zhenghe Song.


international conference on automation and logistics | 2007

Image Segmentation Based on Ant Colony Optimization and K-Means Clustering

Bo Zhao; Zhongxiang Zhu; Enrong Mao; Zhenghe Song

According to the characteristics of the ant colony optimization and the K-means clustering, a method for the image segmentation based on the ant colony optimization and the K-means clustering was proposed in this paper. Firstly, the basic principle of the two algorithms were introduced. Secondly, their characteristics on the image segmentation were analyzed. Finally the improved algorithm was proposed, this algorithm can effectively overcome shortages which are the slow rate of the ant colony optimization and the K-means clustering dependent on the initial clustering centers. Experimental results proved that the improved algorithm was an effective method for the image segmentation in the practical application, which could segment the object accurately.


international conference on machine learning and cybernetics | 2007

Research on Traffic Number Recognition Based on Neural Network and Invariant Moments

Zhenghe Song; Bo Zhao; Zhongxiang Zhu; Enrong Mao

Traffic number recognition is the important and essential content on license plate recognition and traffic sign recognition. A method of traffic number recognition based on the neural network and the invariant moments was proposed in this paper. Firstly, the area of the traffic number was located from the complicated image background and each number was taken by the image segmentation. Secondly, the features of each number were obtained by Hu invariant moments, which are the invariability of the translation, the ratio and the rotation, and have lower computational complexity. Finally, the traffic number was recognized by the BP neural network. Experimental results proved that the proposed method can be used for fast and efficient recognition of the traffic number with high accuracy.


international conference on machine learning and cybernetics | 2007

Study on Crop Image Feature Extraction of Vehicle-Based Estimation System on Large Scale Crop Acreage

Suxia Wang; Zhenghe Song; Zhongxiang Zhu; Bangjie Yang; Enrong Mao; Rui Zhang

Vehicle-based estimation system on large scale crop acreage, which was equipped with GPS receivers, GIS software and a video camera on a off-road vehicle, can capture the images of video and calculate the crop acreage proportion based on matching between GPS information and image recognition. The system provides the credible data for government to make decision and provides technological method. In order to enhance the real-time and reliable character of the system, namely improve the precision of image recognition and estimation result, the grid algorithm of the crop image feature extraction was proposed. The principle of the grid algorithm was that the every crop image was segmented to 16 grids averagely and the four corner grids were regarded as the beginning area during feature extraction and crop recognition. Whether or not to continue extracting feature and recognizing in other grids as well as the recognizing sequence was determined according to the result of crop recognition in the four beginning areas. The texture feature, the shape feature and the color feature were extracted in terms of the particularity of the crop recognition, then the different features or the feature combination were used in order to recognize the crop. The detailed analysis methods of different crops and different cultivating condition were discussed in this paper.


computational intelligence | 2009

Expert System for Tractor Cab Man-Machine Interface Evaluation

Xiao-yan Yan; Zhenghe Song; Zhongxiang Zhu; Enrong Mao

The expert system for tractor cab man-machine interface evaluation was developed using Visual C++ and CLIPS that is one of the expert system tools on the re-development platform of CATIA. The system structure and functions were presented. The knowledge expression, reason mechanism and the design and build method of knowledge base were put forward. The expert system can be used to evaluate the man-machine interface of tractor cab quickly and find the shortage of design. Finally, some improvement suggestions were given by the system. Experiments were carried out for a tractor model. The results showed that the expert system could evaluate the tractor model man-machine interface effectively.


international conference on mechatronics and automation | 2007

Control System for Tractor-Platooning

Zhongxiang Zhu; Jun-ichi Takeda; Ryo Torisu; Jun Chen; Zhenghe Song; Enrong Mao

A control system for two-tractor platooning was developed, which dealt with follow-up motions for both straight and curvous courses. Firstly, a trajectory of the leading tractor was dynamically obtained by processing the position points of the leading tractor with the method of least squares and curve fitting. Secondly, based on the vehicle kinematic model, a reference course for the following tractor was dynamically created from the trajectory of the leading tractor with a given lateral offset. Finally, an optimal path-tracking controller was designed to guide the following tractor along the reference course. Field tests were conducted on a flat meadow. The test results indicated that the following tractor followed up the leading tractor successfully. The mean and RMS lateral deviations for the straight course were 0.02 and 0.02 m, respectively, whereas those for the sinusoidal course were 0.02 and 0.04 m, respectively.


international conference on machine learning and cybernetics | 2007

Vision System Calibration of Agricultural Wheeled-Mobile Robot Based on BP Neural Network

Bo Zhao; Zhongxiang Zhu; Enrong Mao; Zhenghe Song

Camera calibration is the base of the machine vision based the autonomous navigation of the agricultural wheeled-mobile robots. There are the complex nonlinear relationship between the actual position points and the matched image points. Therefore the camera parameters have to be calculated by a precise imaging model. The more precise the imaging model requires, the more complicated the calibration becomes. It was proved that some traditional calibration methods, such as the method of Zhengyou Zhang, were inconvenient and their accuracy were also low. In this paper, according to the characteristic of the BP neural network, which can express any nonlinear relationship between inputs and outputs, a new method based on the BP neural network was applied to calibrate the vision system of an agricultural wheeled-mobile robot. The experimental results showed that this method was feasible and accurate.


Journal of Zhejiang University Science C | 2016

Proportional directional valve based automatic steering system for tractors

Jin-yi Liu; Jing-quan Tan; Enrong Mao; Zhenghe Song; Zhongxiang Zhu

Most automatic steering systems for large tractors are designed with hydraulic systems that run on either constant flow or constant pressure. Such designs are limited in adaptability and applicability. Moreover, their control valves can unload in the neutral position and eventually lead to serious hydraulic leakage over long operation periods. In response to the problems noted above, a multifunctional automatic hydraulic steering circuit is presented. The system design is composed of a 5-way-3- position proportional directional valve, two pilot-controlled check valves, a pressure-compensated directional valve, a pressurecompensated flow regulator valve, a load shuttle valve, and a check valve, among other components. It is adaptable to most open-center systems with constant flow supply and closed-center systems with load feedback. The design maintains the lowest pressure under load feedback and stays at the neutral position during unloading, thus meeting the requirements for steering. The steering controller is based on proportional-integral-derivative (PID) running on a 51-microcontroller-unit master control chip. An experimental platform is developed to establish the basic characteristics of the system subject to stepwise inputs and sinusoidal tracking. Test results show that the system design demonstrates excellent control accuracy, fast response, and negligible leak during long operation periods.


international conference on computer and computing technologies in agriculture | 2010

Virtual Reality and the Application in Virtual Experiment for Agricultural Equipment

Yu Zang; Zhongxiang Zhu; Zhenghe Song; Enrong Mao

The meaning and characteristics of the virtual experiment and the significance of applying virtual prototype into agricultural equipment were analyzed in this paper. Then a kind of virtual experiments system platform on agricultural equipments was founded by using MultiGen Creator, Vega Prime software and VC++ programming language. According to the functions of the virtual experiment system, the structure and all components of the system were introduced. Furthermore, the methods of network design, synchronous driving, image edge-blending and geometric calibration, and the key technologies such as tractors dynamics modeling, experiment reappearance and real-time test of virtual experiment were discussed. Finally, based on three-dimension geometry model and Vega Prime, the digitalization of tractor testing ground and real-time performance simulation were realized, which provides a new research means and technical method for the tractor performance testing. The test results show that the platform could make the observers immersed among the virtual environment to experience testing process directly and intuitively, and could achieve the real-time interaction between users and environment. This study proves stable operation of the system with reliability and validity, its velocity can reach 30 frames/s and the delay time is 0.025s.


International Conference on Mechanical Design | 2017

An Alternative Inverse Kinematics Position Analysis for the Control of Welding Robot

Wenjuan Li; Yuefeng Du; Zhenghe Song; Xueyan Zhao; Enrong Mao

Welding robot is a manipulator which is analyzed and applied widely. It’s important to obtain the values of the robot joints when the position of end-effector is settled. In the design preliminary stage, or any other stages without a manipulator or a teach pendant as the real model, it’s necessary to develop the analysis method and algorithm to obtain the configuration of robot and simulate the control process, according to the robot parameters. In this paper, firstly the inverse kinematics analysis based on analytic expressions was developed to obtain the functional expression of each joint. Then based on the expressions, the algorithm was proposed to calculate all the exact values with the position of end-effector settled. The algorithm was realized by programming in MATLAB, making it easy to get the solutions of each joint, which provided the basic data for controlling. Finally we presented the control functions during a specific trajectory as example, considering the principle of minimum energy consumption. The result of this method is proved to be correct and the procedure is effective and fast. With the method one can analyze all the admissible configurations of the robot conveniently and obtain the control functions of robot joints to keep the end-effector in a specific trajectory.


international conference on mechanic automation and control engineering | 2012

Virtual Prototyping Analysis on Gear Assembly of the Power Train for a Large-scale Combine Harvester

Zhen Li; Zhongxiang Zhu; Bin Xie; Shourong Liu; Ruijuan Chi; Zhenghe Song; Enrong Mao

Stabilization of the operating speed is a vital factor that affects a combine harvesters productivity. In this paper, the pretreatment of CAD models is set for precise simulation. Using CAE tools, the research concentrates on the static and kinematic characters of the gear assembly in the power train. Ultimately, the comparisons of the simulation results with the theoretical ones are conducted. The results indicate that the designed gear assembly can remain the operating speed stable and reliable under the assumed condition.

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Zhongxiang Zhu

China Agricultural University

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Enrong Mao

China Agricultural University

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Bin Xie

China Agricultural University

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Yuefeng Du

China Agricultural University

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Suxia Wang

China Agricultural University

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Jin-yi Liu

China Agricultural University

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