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Natural Gas TEG Dehydration Equipment Digital Twin and Condition Evaluation
- Citation Author(s):
- Submitted by:
- Aijun Yin
- Last updated:
- Tue, 06/18/2024 - 22:08
- DOI:
- 10.21227/3vte-gm80
- License:
97 Views- Categories:
- Keywords:
Abstract
This dataset is data support for a research paper named “Natural Gas Triethylene Glycol Dehydration Equipment Digital Twin and Condition Evaluation Application”. The paper has been submitted to IEEE Transactions on Industrial Informatics.
In the paper, a natural gas dehydration process digital twin (DT) is proposed for condition evaluation. The framework and detailed DT models are introduced. The geometric, process, behavioral and rule models in DT map physical entities geometric information, working process, control process, and hidden condition evolution process, respectively. A triethylene glycol (TEG) dehydration DT application system is developed and the overall reality-virtual mapping process of DT for equipment condition evaluation is demonstrated.
In the dataset, equipment historical monitoring data, TEG dehydration HYSYS simulation model, fault diagnosis and parameter prediction algorithms, DT software description are provided to concretize our work and make sure researchers in related fields can reproduce it.
Copyright:
Professor Aijun Yin
College of Mechanical and Vehicle Engineering
Chongqing University
Email: aijun.yin@cqu.edu.cn
This dataset is data support for a research paper named “Natural Gas Triethylene Glycol Dehydration Equipment Digital Twin and Condition Evaluation Application”. The paper has been submitted to IEEE Transactions on Industrial Informatics.
In the paper, a natural gas dehydration process digital twin (DT) is proposed for condition evaluation. The framework and detailed DT models are introduced. The geometric, process, behavioral and rule models in DT map physical entities geometric information, working process, control process, and hidden condition evolution process, respectively. A triethylene glycol (TEG) dehydration DT application system is developed and the overall reality-virtual mapping process of DT for equipment condition evaluation is demonstrated.
In the dataset, equipment historical monitoring data, TEG dehydration HYSYS simulation model, fault diagnosis and parameter prediction algorithms, DT software description are provided to concretize our work and make sure researchers in related fields can reproduce it.
Copyright:
Professor Aijun Yin
College of Mechanical and Vehicle Engineering
Chongqing University
Email: aijun.yin@cqu.edu.cn
