The Study On Attitude And Orbit Automatic Control System Of EPB Shield Machine

Shield tunneling machine is special engineering machinery used for underground construction projects. Earth pressure balance shield (EPBS), as the most widely used shield, is suitable for a variety of tunnel projects. EPBS uses cabin sealed in front of the machine to stable the cutting surface. The hydraulic cylinders push the machine forward while the cutter cutting the soil. The accurate prediction and control of the EPBS attitude make sure that the boring trajectory and the axis of the tunnel are in the same direction.Modern EPBS is a kind of intelligent large-scale construction machinery and equipment, which is an integration of mechanical, electrical, hydraulic, control, information technology. Based on the characteristics of EPBS construction, as well as the problems of attitude and trajectory control, the main research contents are as follows:(1). Based on characteristics of the EPBS, the composition and construction principles are described. This paper discusses the role of each the components of EPBS and proposes attitude and trajectory control parameters of EPBS, the measurement of parameters and control strategies.(2). An Earth pressure balance shield automatic control system is designed. An automatic control system by Siemens PLC is designed, and the system’s hardware and software are well designed. This paper also designs the control function for the earth pressure balance shield construction process requirements.(3). A load model of earth pressure balance shield machine is proposed. Factors which affect the attitude of EPBS are taken full account. This paper studies the impact of the load on the EPBS and establishes the load model.(4). A neural network expert system of attitude control is established. According to the characteristics of EPBS, a neural network expert of attitude control is proposed. The formation parameters, the shield machine parameters and the initial attitude data are stored in a neural network expert system as knowledge base. We can use this neural network expert system for reasoning to predict changes in shield attitude parameters. Simulation results show that the neural network expert system has good prediction accuracy and the prediction can be used to compensation control of shield machine attitude parameters.