【作者】 魏盈盈；

【导师】 刘亚秋；

【作者基本信息】 东北林业大学 ， 计算机应用技术， 2011， 硕士

【摘要】 随着我国森林资源的紧缺,人造板的生产已经受到板材生产企业的充分重视。刨花板以其生产和使用的种种优点,给刨花板生产企业的发展带来了前所未有的良机。刨花板生产中影响板材最终产品质量的重要步骤是热压工序。论文以刨花板热压工艺为研究对象,分别从板坯内部热质传递和热压位置伺服控制两方面进行深入研究。由于实际生产中板坯芯层温度难以测量,本文借助BP (Back Propagation)神经网络自学习能力,通过训练已有的实验数据,来预测板坯芯层的导热参数从而推导出板坯芯层温度。并用改进的ELM (Extreme Learning Machine-ELM)算法进一步提高了预测精度。所得的导热性能预测方法可以改进实际生产中的实时热压控制工艺。在研究了热压机相关工作原理的基础上,以刨花板热压机为控制对象,针对热压位置控制存在的非线性特性及平稳无超调控制的特殊工艺要求,提出采用模糊自适应的控制方法对板坯厚度进行控制。该方法通过模糊优化输入参数对热压控制器实施在线自整定,得以提高刨花板热压机控制器的控制能力。通过MATLAB计算机仿真研究,验证上述理论结果。先与常规位置伺服PID控制器进行对比,验证了模糊自适应位置伺服控制器在不同组初值的情况下均能达到迅速稳定和无超调的响应,显著提升了刨花板热压机的位置伺服控制系统的稳定性及控制精度。热压控制不应单一考虑热压机的位置控制,还应充分考虑热压过程中热质扰动对板坯内部环境的影响。因此,在本控制系统中增加了抗扰动模糊模块。通过仿真结果表明,加入抗扰动模糊模块之后,位置伺服控制系统的抗干扰能力明显增强,提高了最终板材产品的质量。更多还原

【Abstract】 With the shortage of wood resources, people are increasingly paying attention to wood-based panel production. Particleboard has brought about new opportunities and challenges to the development of particleboard industry by its own advantages. In particleboard production process, hot-pressing is one of the most important processes. It directly influences the quality and the yields of the final board products. To particleboard hot-pressing process as the research object, this paper respectively from two aspects of the slab heat and mass transfer and the position servo control have been studied.It is difficult to measure the slab core temperature in the actual production. Through self-learning ability of Back Propagation neural network and training of existing experimental data, this sets up a model of forecast the thermal conductivity under various conditions. In order to improve the prediction precision, Extreme Learning Machine is introduced into this model. At the same time, this research has a certain significance in the future actual production.According to some phenomena such as non-linear characteristic, the special process requirements of steady control without overshoot, and base on the principle of the pressing machine, we adopt the fuzz self-tuning strategy to control the slab thickness. The method can improve control precision and stabilization of the electro-hydraulic position servo system, which by fuzzy optimization implement parameters online self-tuning.MATLAB computer simulation verifies the theoretical results. First of all, compared with the conventional PID controller, the fuzzy adaptive controller in the case of the initial value can be fast stable and no oyershoot response, which markedly improved the particleboard hot-pressing control accuracy and stability in the servo control system. Hot-pressing control not only should consider the location of a single control process, but also should take account of the heat and mass disturbance effect within the slab. Therefore, the system increased thermal mass anti-disturbing fuzzy module. The simulation results show that the addition of anti-disturbing fuzzy module, the position servo control system significantly enhanced anti-disturbing capability and improved the quality of the final particleboard products.更多还原