EconPapers    
Economics at your fingertips  
 

Digital twins-based process monitoring for wastewater treatment processes

Wentao Liu, Sudao He, Jianpeng Mou, Ting Xue, Hongtian Chen and Weili Xiong

Reliability Engineering and System Safety, 2023, vol. 238, issue C

Abstract: Digital twins are a significant way to achieve fault detection of various smart manufacturing, which provide a new paradigm for complex industrial process monitoring. Wastewater treatment processes play a crucial role in water recycling, its failures may cause risks of adverse environmental impacts. This paper studies the digital twins fault detection framework based on the convolutional autoencoder for wastewater treatment processes monitoring. The designed digital twins fault detection framework can simulate the sludge bulking failure and the toxic impact failure conditions in the virtual space to construct the simulation data with continuous updating through wastewater data. The simulation data is divided into rate of change information sub-block, original sub-block, and cumulative information sub-block using the multi-block modeling strategy to fully explore the hidden information. Further, the sliding window method is utilized to resample the reconstructed sub-blocks to enhance the effects of the detection performance. Bayesian fusion is adopted, and the final decision is made based on the fused statistical value and the control limit. The comparison experiments tested on the digital twins fault detection framework demonstrate the superiority and feasibility of detection performance.

Keywords: Digital twins; Fault detection; Wastewater treatment processes; Convolutional autoencoder (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832023003307
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:238:y:2023:i:c:s0951832023003307

DOI: 10.1016/j.ress.2023.109416

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:reensy:v:238:y:2023:i:c:s0951832023003307