scholarly journals Label propagation dictionary learning based process monitoring method for industrial process with between-mode similarity

2021 ◽  
Vol 65 (1) ◽  
Author(s):  
Keke Huang ◽  
Shijun Tao ◽  
Yishun Liu ◽  
Chunhua Yang ◽  
Weihua Gui
Keyword(s):  
Process Monitoring ◽  
Dictionary Learning ◽  
Industrial Process ◽  
Label Propagation ◽  
Monitoring Method

Distributed dictionary learning for industrial process monitoring with big data

2021 ◽  
Author(s):  
Keke Huang ◽  
Ke Wei ◽  
Yonggang Li ◽  
Chunhua Yang
Keyword(s):  
Big Data ◽  
Process Monitoring ◽  
Dictionary Learning ◽  
Industrial Process

scholarly journals An Efficient Quality-Related Fault Diagnosis Method for Real-Time Multimode Industrial Process

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Kaixiang Peng ◽  
Bingzheng Wang ◽  
Jie Dong
Keyword(s):  
Fault Diagnosis ◽  
Process Monitoring ◽  
Industrial Process ◽  
Hot Strip Mill ◽  
Gaussian Component ◽  
Contribution Rate ◽  
Process Data ◽  
Monitoring Method ◽  
Projection To Latent Structures ◽  
Latent Structures

Focusing on quality-related complex industrial process performance monitoring, a novel multimode process monitoring method is proposed in this paper. Firstly, principal component space clustering is implemented under the guidance of quality variables. Through extraction of model tags, clustering information of original training data can be acquired. Secondly, according to multimode characteristics of process data, the monitoring model integrated Gaussian mixture model with total projection to latent structures is effective after building the covariance description form. The multimode total projection to latent structures (MTPLS) model is the foundation of problem solving about quality-related monitoring for multimode processes. Then, a comprehensive statistics index is defined which is based on the posterior probability of the monitored samples belonging to each Gaussian component in the Bayesian theory. After that, a combined index is constructed for process monitoring. Finally, motivated by the application of traditional contribution plot in fault diagnosis, a gradient contribution rate is applied for analyzing the variation of variable contribution rate along samples. Our method can ensure the implementation of online fault monitoring and diagnosis for multimode processes. Performances of the whole proposed scheme are verified in a real industrial, hot strip mill process (HSMP) compared with some existing methods.

scholarly journals A Robust Transfer Dictionary Learning Algorithm for Industrial Process Monitoring

Engineering ◽  
2021 ◽  
Author(s):  
Chunhua Yang ◽  
Huiping Liang ◽  
Keke Huang ◽  
Yonggang Li ◽  
Weihua Gui
Keyword(s):  
Process Monitoring ◽  
Dictionary Learning ◽  
Learning Algorithm ◽  
Industrial Process

A geometry constrained dictionary learning method for industrial process monitoring

2021 ◽  
Vol 546 ◽  
pp. 265-282
Author(s):  
Keke Huang ◽  
Haofei Wen ◽  
Han Liu ◽  
Chunhua Yang ◽  
Weihua Gui
Keyword(s):  
Process Monitoring ◽  
Dictionary Learning ◽  
Industrial Process ◽  
Learning Method

Industrial process monitoring by synthetic view

2007 ◽  
Author(s):  
Antonio Dourado ◽  
Paulo Barbeiro ◽  
Edgar Ferreira ◽  
Jorge Henriques ◽  
Maria Antonio ◽  
...  
Keyword(s):  
Process Monitoring ◽  
Industrial Process ◽  
Synthetic View
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