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改進的主元分析法在連鑄結晶器過程監測中的應用

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

  • 摘要: 將改進的主元分析(PCA)方法應用于連鑄結晶器的過程監測.基于板坯連鑄結晶器摩擦力實測數據進行仿真分析,結果表明,改進的PCA避免了Q統計量的保守性,從而能夠更有效地識別過程故障與工況改變引起的T2統計量的變化.與傳統的PCA方法相比,改進PCA具有更強的故障檢測能力.

     

    Abstract: 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 T2 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.

     

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