Predictive warning system for nonlinear process plants

Khan, M. Abdesh; Imtiaz, Syed; Khan, Faisal

doi:10.1016/j.jprocont.2021.01.008

Cited by 3 publications

(1 citation statement)

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“…Continuous Stirred Tank Reactor. As a benchmark, the continuous stirred tank reactor (CSTR) 39,40 is used to testify the proposed methodology in this section. This simulation system consisted of feed stream containing reactant stream, product stream, and cooling water stream.…”

Section: Process Monitoring Based On Esffmentioning

confidence: 99%

Linear Chain Conditional Random Field for Operating Mode Identification and Multimode Process Monitoring

Wang

2022

ACS Omega

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As a supervised machine learning algorithm, conditional random fields are mainly used for fault classification, which cannot detect new unknown faults. In addition, faulty variable location based on them has not been studied. In this paper, conditional random fields with a linear chain structure are utilized for modeling multimode processes with transitions. A linear chain conditional random field model is trained by normal data with mode label. This model is able to distinguish transitions from stable modes well. After mode identification, the expectation of state feature function is developed for fault detection and faulty variable location. Case studies on the Tennessee Eastman process and continuous stirred tank reactor (CSTR) testify the effectiveness of the proposed approach.

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Section: Process Monitoring Based On Esffmentioning

confidence: 99%