CN106094786B - 基于集成型独立元回归模型的工业过程软测量方法 - Google Patents
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
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- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
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Families Citing this family (11)
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CN106599494B (zh) * | 2016-12-07 | 2019-08-16 | 宁波大学 | 基于多重动态plsr模型的产品质量软测量方法 |
CN107025351B (zh) * | 2017-04-01 | 2019-08-16 | 宁波大学 | 一种基于多近邻保持嵌入回归模型的工业软测量方法 |
CN107478418A (zh) * | 2017-06-29 | 2017-12-15 | 南京航空航天大学 | 一种旋转机械故障特征自动提取方法 |
CN108170648B (zh) * | 2017-12-15 | 2021-05-18 | 宁波大学 | 一种基于已知数据回归的非高斯过程监测方法 |
CN108181894B (zh) * | 2017-12-15 | 2020-11-24 | 宁波大学 | 一种基于修剪独立元回归策略的非高斯过程监测方法 |
CN108492026B (zh) * | 2018-03-06 | 2021-05-11 | 宁波大学 | 一种基于集成正交成分最优化回归分析的软测量方法 |
CN108445867B (zh) * | 2018-03-06 | 2020-06-16 | 宁波大学 | 一种基于分散式icr模型的非高斯过程监测方法 |
CN108520111B (zh) * | 2018-03-06 | 2021-11-30 | 宁波大学 | 一种基于正交成分最优选择与最优回归的软测量方法 |
CN111650894A (zh) * | 2020-04-02 | 2020-09-11 | 中国计量大学 | 一种基于隐变量的贝叶斯网络复杂工业过程软测量方法 |
CN111581792B (zh) * | 2020-04-23 | 2021-01-08 | 生态环境部环境规划院 | 一种基于两阶段非负Lasso模型的大气PM2.5浓度预测方法及*** |
CN113012766B (zh) * | 2021-04-27 | 2022-07-19 | 昆明理工大学 | 一种基于在线选择性集成的自适应软测量建模方法 |
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CN1693892A (zh) * | 2005-04-13 | 2005-11-09 | 华东理工大学 | 乙炔加氢反应器一段出口乙炔浓度的在线软测量方法 |
JP4600237B2 (ja) * | 2005-10-04 | 2010-12-15 | 富士ゼロックス株式会社 | 故障診断システム、画像形成装置及び故障診断方法 |
CN101158693B (zh) * | 2007-09-26 | 2011-08-17 | 东北大学 | 基于多核独立元分析的批量生产过程故障检测方法 |
CN100565403C (zh) * | 2007-09-26 | 2009-12-02 | 东北大学 | 一种非线性过程故障诊断方法 |
CN101419216B (zh) * | 2008-10-16 | 2012-06-27 | 浙江工业大学 | 基于gp学习建模的发酵制药产物质量软测量方法 |
CN101630376B (zh) * | 2009-08-12 | 2012-06-20 | 江苏大学 | 多模型神经网络的生物发酵过程软测量建模方法及软仪表 |
CN103390103A (zh) * | 2013-07-15 | 2013-11-13 | 浙江大学 | 基于子空间独立成分回归模型的熔融指数在线检测方法 |
CN103440368B (zh) * | 2013-08-12 | 2017-06-13 | 上海交通大学 | 一种多模型动态软测量建模方法 |
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