一种新型偏差参数模糊融合法及其在加热炉中的应用

A Novel Fuzzy Fusion Method Based Deviation and Its Application on Furnace

为了提高直接式加热炉在安全性、平稳性、出炉温度精度等方面的性能 ,一种新型的偏差参数融合方法被提出。加热炉是一个多输入、多输出系统 ,并且各参数间是强耦合的。该文利用加热炉这一动态特性 ,把现场采集一些相关的加热炉参数的偏差作为改进的模糊算法的输入参数 ,该模糊算法充分考虑到各采集传感器故障情况。输出结果与各输入偏差比较可以在线辨识传感器故障和火嘴偏烧情况。该融合方法还考虑了传感器精度、原油偏流以及火嘴偏烧等因素对原油出炉温度的影响 ,使原油出炉温度的融合结果精度更高 ,原油出炉温度精度可以提高0 5℃。该方法可以推广应用到有动态特性的系统中。

In order to improve performance on security, stability and accuracy of oil outlet temperature in the direct furnace, a novel fuzzy fusion method based on the deviation is proposed. The direct furnace is a dynamic system. which input multiple variables and output miltiple variables are strong coupled. Based on the furnace features. the improved fuzzy method uses the deviation of some correlative parameters that acquired from furnace as input parameters, which thinks over possibility of sensors fault. Then the change of the trend of furnace can be gotten. which is used to identify faulty sensors in the furnace and fire nozzle deflection. The sensors precision. asymmetric flow of two oil pipeline and fire nozzle deflection are also taken into account in the fusion method. thereby the fusion result of oil pipeline. Experimental results indicate that the accuracy of oil outlet temperature can be advanced about 0.5℃.The method can abroad apply to other dynamic system.