改进的主元分析法在连铸结晶器过程监测中的应用

Application of improved principal component analysis method to mould process monitoring in continuous casting

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） was introduced to the monitoring of mould processes during slab continuous casting. Based on analyzing the measured mould friction data, simulation results show that the improved PCA can avoid the conservation of Q statistical test and effectively identify the change in the Hotelling T^2 test which may caused by process fault or variation in operating condition. Compared with the conventional PCA, the improved PCA is more effective and sensible in fault diagnosis and process monitoring.