Research On Intelligent Control System Of Bridge Prestressed Tensioning Equipment

Prestressed concrete plays an important role in construction projects and has been extensively and deeply developed in the process of infrastructure construction in contemporary China.With the general trend of national industrial upgrading and the continuous improvement of construction standards,it has become an urgent need to develop control systems for prestressed construction equipment with higher precision and performance,as well as to realize construction informationization.In engineering practice,the existing prestressed tensioning equipment control system mainly includes manual electrical control type and a variety of automatic control system types.Manual electrical control type prestressed tensioning equipment in the construction process depends entirely on the experience of personnel visual control of the corresponding instrument,prestressed tension control of the construction parameters in the construction process is difficult;PLC automatic control system can achieve data acquisition and automatic tensioning,but the control process control accuracy in the construction process is not enough,it is difficult to achieve high precision synchronization;The embedded automation type prestressing tensioning equipment greatly reduces the hardware cost of the equipment control system,but increases the difficulty of system development and the intelligent control algorithm is still not able to guarantee higher control precision.In this paper,an intelligent control system based on improved BP neural network PID control algorithm combined with information technology is proposed.The control system includes a host controller PLC,a tension control terminal control software and a remote server data management software.The control system uses high-precision pressure sensors and displacement sensors to collect construction process data in real time and send it as a control input to the main controller.The main PLC respectively sends the data to the tension control terminal and the remote server through the wireless communication,which can make the construction data have higher real-time and accuracy;The control system indirectly controls the output speed of the hydraulic pump by controlling the rotational speed of the hydraulic pump drive motor so as to indirectly control the control parameters of the tension control stress and elongation;Tension control software installed in the tension control terminal equipment,with real-time data display,parameter setting and other human-machine interaction function,mounting an improved BP neural network algorithm PID parameters online real-time tuning,to achieve a higher level of construction.In this paper,the PID controller of BP neural network is improved and simulated by MATLAB.Simulation results show that the algorithm improves the convergence speed and control performance.The control system is used for small-scale equipment deployment and practical test on the project site The test results are compared with the traditional automatic prestressing tensioning equipment.Test results and the use of traditional equipment for comparative study,the results verify that the system with control accuracy and synchronization have greatly improved,fully validated the effectiveness of the system and high engineering applicability.