局部近邻标准化偏最小二乘的多模态间歇过程故障检测
本文针对多模态间歇过程数据多中心和模态方差差异明显的问题,提出了一种基于局部近邻标准化偏最小二乘方法.首先,采用统计模量方法处理间歇过程数据,再利用局部近邻标准化方法将统计模量后的训练数据进行高斯化处理,建立偏最小二乘监控模型,确定控制限;然后,同样对统计模量后的测试数据进行局部近邻标准化处理,再计算测试数据的高斯偏最小二乘监控指标,进行过程监视及故障检测.最后,通过数值实例和青霉素发酵过程验证方法有效性.实验结果表明所提方法解决了故障样本近邻集跨模态问题,对多模态数据具有更好的故障检测能力....
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| Published in | 控制理论与应用 Vol. 37; no. 5; pp. 1109 - 1117 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
沈阳化工大学信息工程学院,辽宁沈阳,110142%沈阳化工大学数理系,辽宁沈阳,110142
01.05.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-8152 |
| DOI | 10.7641/CTA.2019.80725 |
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| Abstract | 本文针对多模态间歇过程数据多中心和模态方差差异明显的问题,提出了一种基于局部近邻标准化偏最小二乘方法.首先,采用统计模量方法处理间歇过程数据,再利用局部近邻标准化方法将统计模量后的训练数据进行高斯化处理,建立偏最小二乘监控模型,确定控制限;然后,同样对统计模量后的测试数据进行局部近邻标准化处理,再计算测试数据的高斯偏最小二乘监控指标,进行过程监视及故障检测.最后,通过数值实例和青霉素发酵过程验证方法有效性.实验结果表明所提方法解决了故障样本近邻集跨模态问题,对多模态数据具有更好的故障检测能力. |
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| AbstractList | 本文针对多模态间歇过程数据多中心和模态方差差异明显的问题,提出了一种基于局部近邻标准化偏最小二乘方法.首先,采用统计模量方法处理间歇过程数据,再利用局部近邻标准化方法将统计模量后的训练数据进行高斯化处理,建立偏最小二乘监控模型,确定控制限;然后,同样对统计模量后的测试数据进行局部近邻标准化处理,再计算测试数据的高斯偏最小二乘监控指标,进行过程监视及故障检测.最后,通过数值实例和青霉素发酵过程验证方法有效性.实验结果表明所提方法解决了故障样本近邻集跨模态问题,对多模态数据具有更好的故障检测能力. |
| Author | 李元 马雨含 冯立伟 张成 |
| AuthorAffiliation | 沈阳化工大学信息工程学院,辽宁沈阳,110142%沈阳化工大学数理系,辽宁沈阳,110142 |
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| Author_FL | LI Yuan FENG Li-wei ZHANG Cheng MA Yu-han |
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| Keywords | 局部近邻标准化 故障检测 多模态间歇过程 偏最小二乘 |
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