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The Intelligent Self-Learning Leveling Model And The Electro-Hydraulic Servo Control Theory Of The Full-Hydraulic Leveler

Posted on:2014-05-02Degree:DoctorType:Dissertation
Country:ChinaCandidate:H J ZhangFull Text:PDF
GTID:1261330401977078Subject:Mechanical and electrical engineering
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In recent years, with the rapid development of China’s iron and steel industry, the requirements on the unflatness accuracy of the steel plate for the customers has been getting higher and higher, which makes the quality requirements of the leveler higher and higher for the iron and steel enterprises. The core technology of the leveling equipment, such as the intelligent leveling model and electro-hydraulic servo control etc., has been blocked by the leveler manufacturers abroad, and there is still a considerable gap in the straightening efficiency and straightened plate qulity between domestic leveler and the foreign same type equipment. Which makes the most large domestic steel manufacturers have invested heavily in the introduction of foreign advanced equipment for the production needs. Therefore, the localization of the new generation powerful intelligent leveler has become the top priority of the domestic leveler manufacturers. The core technology of the new generation powerful intelligent leveler is the multi-hydraulic-cylinder synchronous servo control technology and the intelligent self-learning leveling model. In this paper, based on four-heavy-style11-roll thermal leveler of a steel rolling line of domestic some steel producer and with reference to the levelers of other heat treatment line, multi-hydraulic-cylinder decoupling control model and its control algorithms, intelligent self-learning leveling model, of China’s new generation powerful intelligent leveler have been established. Based on modeling, simulation and actual application, the following research has been made.(1)The existing transfer function models of hydraulic servo control system of the domestic leveler and abroad have been carried out a detailed analysis, and their research inadequacies and achievements have been gotten in this article. The existing multi-hydraulic-cylinder synchronous control decoupling methods have been analyzed and their advanteges and disadvantages have been obtained. The leveling models of domestic levelers and abroad levelers have been studied and their inadequacies have been gained. All of above gives a full preparation to solve the two key problems of the localization of the third generation powerful intelligent leveler.(2)According to the engineering practice, the control voltage of the high frequency response proportion servo valve is treated as the input signal and the displacement of the hydraulic cylinder piston is treated as the output signal. And the valve-control-cylinder transfer function model has been founded based on the high frequency response asymmetric proportional servo valve controlling asymmetric cylinder. It is different from a conventional transfer function model in which the spool bias of the servo valve is treated as the input signal. So the transfer function is more realistic in this paper. On the above, the four-cylinder control model has been derived and obtained.(3)A "combined given curve" has been designed and it can reduce the shocks of the system with the large mass and inertia at the start and end of the movement process. An improved single control variable neuron controller and an improved multiple control variables neuron controller have been established. The stability of the multiple control variables neuron controller has been proved and the weight value of the neuron controller is optimized using the particle swarm optimization algorithm. By the simulation of. the established single-cylinder and multi-cylinder servo control object transfer function models, the results show that the multi-cylinder displacement process synchronization error maximum is0.18mm, steady-state synchronization error maximum is0.15mm, speed process synchronization error maximum is0.1mm/s. it has been proved effective and practical for the improved multiple control variables neuron controller to decouple the multi-cylinder coupling control system of the full-hydraulic leveler.(4)The leveling model of the full-hydraulic leveler has been established by the analytic method and on this basis the superimposition of the bending roller and the side roller has been added to the roll reduction of the leveler. And the leveling force estimated formula of the reinforced plate has been deduced and established. Based on the structural parameters of the actual leveler, a algorithm instance for the use of the leveling model has been given for a certain type of plate.(5)Based on the fuzzy control theory, by the knowledge summary of the leveling process expert and the established analytical model, the intelligent self-learning leveling model of the full-hydraulic leveler has been established. By the assumption to the actual leveling process, for a certain type of plate after straightened, the learning result of the intelligent self-learning system comes to the approximate same learning outcome from the operators and craft persons of the full-hydraulic leveler. The fuzzy compensations of the entrance and export roll gap are all1.02mm, and the compensation of the entrance gap is1.20mm and the compensation of the export gap is0.95mm from the craft workers. By comparing the results of the learning system with the craft worker’s experience, a perfect intelligent self-learning leveling model will be obtained and the "no-one" leveling process can be achieved.(6)By the data analysis of the laboratory and field, the requirements of industrial field can fully been met by the new generation powerful intelligent leveler based on the improved multiple control variables neuron controller and intelligent self-learning leveling model in this paper. The displacement synchronization process error maximum is2mm, and the displacement synchronization steady-state error maximum is0.07mm during the four-cylinder big stroke of the laboratoty leveler. The displacement synchronization process error maximum is0.5mm, and the displacement synchronization steady-state error maximum is0.3mm during the four-cylinder big stroke of the industrial site leveler an its maximum bouncing amount is0.25mm during its leveling plate process. Its performance has reached or exceeded the foreign same product.
Keywords/Search Tags:powerful intelligent leveler, the reduction superposition of edgeroller, leveling model of intelligent self-learning, combined given curve, improved multiple control variables neuron controller
PDF Full Text Request
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