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A New Center Position Control Implement

A New Center Position Control Implement

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第二届仪器科学与技术国际学术研讨会

作者： tian qichuan, pan quan, gao quanxue, han rucheng, gao diguang taiyuan heavy machinery inst. Northwestern Ploytechnical Univ.

＜正＞ In many industry-producing fields, CPC （Center Position Control） system is needed to realize automatic control. In this paper, a new CPC implement is presented. It is designed based on single chip microcomputer solving the problem to minimize the quantity of edge-cut. In order to get high precision, new typical high accuracy sensors-CCD （Charge Coupled Device） has been adopted, and a self-adapting adjust hydraulic pressure clique has been used to provide appropriate control. In control algorithm, because the plant is difficult to modeling, a fuzzy control algorithm is used in the system and several parameters are designed to adjust according to the actual running effect in producing locale. Based on this designed, this control system can be used in others similar fields, It has many advantages such as robust, good reliability, high precision, and easy to adjust parameters. Comparison with other control is shown by experimental results and confirms the effectiveness of this control scheme. It has high value being generalized.

关键词： center position control fuzzy control charge coupled device hydraulic pressure system steel belt

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Digital System Fault Diagnosis Based on BP Neural Network

Digital System Fault Diagnosis Based on BP Neural Network

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第二届仪器科学与技术国际学术研讨会

作者： tian qichuan, pan quan, gao diguang, han rucheng, gao quanxue taiyuan heavy machinery inst. Northwestern Ploytechnical Univ.

＜正＞ In this paper, a fault diagnosis strategy of digital system based on BP neural network is presented. After training the neural network can be used to diagnose faults of digital system. Considering tradition BP algorithm of neural network may make weights run into local minimum, A modified algorithm are developed using BP algorithm and applying Metropolis criterion. Finally, this fault diagnosis system has been used in a digital system, the simulation setup is fabricated and tested, and the test results are compared with simulation results. Using this algorithm the approximation error of neural network is very small, and it is an effective approach and efficient in learning. In a conclusion , BP neural network is a good way to complex digital system fault diagnosis.

关键词： BP neural network fault diagnosis digital system fault code Metropolis criterion

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