1. Sub-period division strategies combined with multiway principle component analysis for fault diagnosis on sequence batch reactor of wastewater treatment process in paper mill.
- Author
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Zhou, Jing, Huang, Feini, Shen, Wenhao, Liu, Zhang, Corriou, Jean-Pierre, and Seferlis, Panagiotis
- Subjects
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FAULT diagnosis , *PAPER mills , *WASTEWATER treatment , *BATCH reactors , *SEQUENCING batch reactor process , *PRINCIPAL components analysis - Abstract
• Two sub-period division strategies with MPCA are evaluated in SBR process. • Correlations between the different stages of SBR process are considered. • Four SBR parameters of field data from paper mill are utilized for fault diagnosis. • Sub-period division strategy based on similarity principle demonstrates best. Fault diagnosis of sequential batch reactor (SBR), a widely applied wastewater treatment technology in papermaking industry with huge discharge, has been a significant challenge due to the inherent multi-period characteristics of the process. In this paper, based on the conventional multi-way principal component analysis (MPCA) method (Scenario 0), two sub-period division strategies based on the processing phases of SBR process (Scenario 1) and the similarities of the loading matrices between the adjacent time slices (Scenario 2) are proposed for the detection of faults. Combined with Scenario 0, using the field data of blower current, level of SBR reactor, dissolved oxygen of wastewater and the blower valve opening in the SBR process of paper mill, two different fault diagnosis models with Scenarios 1 and 2 are developed and evaluated, respectively. The study results revealed that, both the calculated statistics of T2 and sum of prediction errors (SPE) of the fault diagnosis models with Scenarios 1 and 2 could detect the faults and identify the fault locations and sources. Compared to Scenario 0 which neglects the correlations between the different stages of SBR process, the fault diagnosis model by Scenario 2 demonstrated a superiority ability in fault identification in terms of the fault's time onset and fault's sources with adequate accuracy. The results enable the feasible and reliable implementation of the developed sub-MPCA diagnosis model with Scenario 2 in the actual SBR plants. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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