Mixture Bayesian regularization method of PPCA for multimode process monitoring 期刊名称： Aiche Journal
作者： Zhiqiang Ge,Zhihuan Song
高考
年份： 2010年
蜜挑
正定大佛寺期号： 第11期
怀孕第一天有什么症状原生欧芙兰关键词： multimode process monitoring; Bayesian regularization; principal
component analysis; model localization零基础学舞蹈
摘要：This article intends to address two drawbacks of the traditional principal component analysis (PCA)-bad monitoring method: (1) nonprobabilistic; (2) single operation mode assumption. On the basis of the monitoring framework of probabilistic PCA (PPCA), a Bayesian regularization method is introduced for performance improvement, through which the effective dimensionality of the latent variable can be determined automatically. For monitoring process with multiple operation modes, t
he Bayesian regularization method is extended to its mixture form, thus a mixture Bayesian regularization method of PPCA has been developed. To enhance the monitoring performance, a novel probabilistic strategy has been propod for result combination in different operation modes. In addition, a new mode localization approach has also been developed,
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