赵小强,周文伟,惠永永

• 1:兰州理工大学电气工程与信息工程学院
• 2:甘肃省工业过程先进控制重点实验室
• 3:兰州理工大学国家级电气与控制工程实验教学中心

摘要(Abstract)：

针对间歇过程的非线性、多模态特性以及质量预测问题,提出多向高斯混合模型-并发核熵潜结构投影(multi-way Gaussian mixture model-concurrent kernel entropy projection to latent structures, MGMM-CKEPLS)算法。首先根据核熵投影将低维非线性数据映射到高维核特征空间,通过Renyi熵贡献的大小选取主元,降低了主元数,克服了传统核方法计算负荷大的问题;然后通过高斯混合模型(GMM)获取每一模态数据,分别对不同模态的样本数建立并发潜结构投影(CPLS)模型,由于考虑了各个模态过程的不同特征,更符合实际间歇过程数据特性;最后通过各模态权值系数集成统一的监控统计量,实现在线监测和质量预测。通过青霉素发酵过程验证了所提算法比MKPLS算法具有更好的在线监控效果,质量预测精度更高。

关键词(KeyWords)： 间歇过程;多模态特性;高斯混合模型;潜结构投影;质量预测

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金(61763029)

作者(Author): 赵小强,周文伟,惠永永

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