淬火、控制冷却的冷却速度和目标温度是关系到钢板性能的关键因素 ,但由于冷却过程的水量、水温、辊道速度等对冷却目标温度的影响属多变量非线性过程 ,用简单的解析模型通常精度较低 ,难以达到精确控制的要求。采用人工神经网络技术对无约束淬火机目标温度进行快速预报 ,结果表明 ,预测精度高 ,快速准确 Quenching and cooling rate control and target temperature are the key factors that affect the performance of the steel plate. However, the influence of the water quantity, water temperature and roller speed on the cooling target temperature is a multivariable nonlinear process. With a simple analytical model Usually low accuracy, difficult to achieve precise control requirements. Artificial neural network technology is used to predict the target temperature of unconstrained quenching machine quickly. The results show that the prediction accuracy is high, fast and accurate