论文部分内容阅读
将改进的主元分析(PCA)方法应用于连铸结晶器的过程监测.基于板坯连铸结晶器摩擦力实测数据进行仿真分析,结果表明,改进的PCA避免了Q统计量的保守性,从而能够更有效地识别过程故障与工况改变引起的T2统计量的变化.与传统的PCA方法相比,改进PCA具有更强的故障检测能力.
The improved principal component analysis (PCA) method is applied to the process monitoring of continuous casting mold.According to the measured data of the friction of slab continuous casting mold, the simulation results show that the improved PCA avoids the conservativeness of Q statistic, Which can more effectively identify the changes of T2 statistics caused by process failure and condition change.Compared with the traditional PCA method, the improved PCA has more fault detection capability.