Modeling and Monitoring Between-Mode Transition of Multimodes Processes

Zhang, Yingwei; Ли, Шуай

doi:10.1109/tii.2012.2220977

Cited by 51 publications

(30 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…18 In multimode processes, different modes have their respective specific, similar characteristics and duration time. 14,15,19 A mode is defined as the long duration process with the same statistical characteristics, which is one part of the whole multimode processes. 7 A simple tutorial example of mode is stated.…”

Section: Preliminariesmentioning

confidence: 99%

Monitoring of Multimode Processes Based on Subspace Decomposition

Ли¹,

Zhou²,

Shi³

et al. 2015

Ind. Eng. Chem. Res.

Self Cite

View full text Add to dashboard Cite

This paper presents a new monitoring method for multimode processes based on subspace decomposition. In the proposed method, the influence of quality variables and multimode information are considered in multimode processes modeling, which is crucially important to ensure industrial production safety and quality stabilization. Process data are decomposed into the global common subspace and the local specific subspace and monitoring is performed in each subspace to simplify the model structure. Two experiments: penicillin fermentation processes and practical foods industrial production processes, have been used to demonstrate the excellent performance of the proposed method.

show abstract

Section: Preliminariesmentioning

confidence: 99%

Monitoring of Multimode Processes Based on Subspace Decomposition

Ли¹,

Zhou²,

Shi³

et al. 2015

Ind. Eng. Chem. Res.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Specially in the beginning stage of the experiment, many undesired alarms are also falsely signaled, which is due to the unstable running in this stage when the system is initialized. For some works focused on monitoring these events, readers can consult literature [51,52]. Meanwhile, comparison study of the detection performance with PLS, T-PLS and C-PLS is also tabulated in Table 3, whereby the detection accuracy entails a ratio by the number of detected faulty samples and the total faulty samples.…”

Section: Tagmentioning

confidence: 99%

Quality-relevant fault detection and diagnosis for hot strip mill process with multi-specification and multi-batch measurements

Peng

Zhang

Dong

et al. 2015

Journal of the Franklin Institute

View full text Add to dashboard Cite

“…By analyzing the relationship between process variables, the available information can be extracted to establish process models for fault detection and diagnosis in industrial processes. Many data-driven monitoring methods have been applied in fault detection and diagnosis to improve the stability of product quality and safety over the past several decades (Yoo et al, 2006;Chen and Zhang, 2010;Ge et al, 2013;Zhang and Li, 2013;Yin et al, 2015).…”

Section: Introductionmentioning

confidence: 99%