弹簧油淬冷却系统的控制算法研究与应用

Research and application of control algorithm for oil cooling system of quenched springs

目前在我国弹簧生产油淬工艺中,工件带入油池的热量和散走的热量没有进行合理的控制,导致油温不稳定,这不仅影响弹簧淬火的质量,而且影响生产过程的稳定性。弹簧油淬冷却系统是一个非线性、时变和滞后的复杂系统,传统的温度控制方法难以获得较好的效果。针对弹簧油淬冷却系统的大超调量、易振荡和低控制精度的特性,设计了模糊BP神经网络控制器。该模糊控制器采用BP神经网络来训练模糊规则,从而达到优化模糊控制器的目的,提高系统的自适应性。最后,将模糊BP神经网络控制方法应用于弹簧油淬冷却系统控制中,取得了良好的控制效果,也满足弹簧油淬的生产要求。

At present the spring production of oil quenching process in our country, the workpiece into the oil pool heat which goes by without reasonable control, leading that oil temperature is not stable, it not only affects the quality of spring after quenching, but also affects the stability of production process. Oil quenching cooling process of spring is a nonlinear, time-varying, lagging complex system, it is difficult for the traditional temperature control method to obtain better results. In view of oil quenching cooling of the system of big overshoot, easy vibration and low control characteristics, a fuzzy controller was designed. The controller uses the neural network to train the fuzzy rules,so as to achieve the optimization of fuzzy controller,improving the adaptive ability of system. Finally, the fuzzy BP neural network control method is applied to spring oil quenching cooling system, and achieves a good control effect, meeting the production requirements of spring oil quenching.