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Internet of Thing System to Extract Hierarchical Healthy and Efficiency Information for Pump Station Optimization

Published: 24 October 2018 Publication History

Abstract

Pump stations provide water supply and dispatching functions in industry plants. Smart and sustainable operations of the pump stations plays a critical role for production safety and efficiency. This requires the real-time states of the pump stations to be tracked for situation awareness. However, the pump stations contain serial/ parallel pumps, pipes, valves, and other devices, whose states are tightly coupled due to the hydrodynamics of the fluid. This paper reports the design, development, and knowledge learned from practical deployment of an Internet of Things (IOT) system in Baotou steel plant, China. We spent more than half a year to deploy a IOT system containing several hundreds of sensor nodes. The IOT system is designed to provide healthy and sustainability information of pump stations in three levels: 1) pump level; 2) pump station level, and 3) system level. The IOT system helps to discover originally unaware problems of the pump stations, and shows potential directions of using IOT and Big data analysis for smart pump station operations.

References

[1]
Maroua Abdelhafidh, Mohamed Fourati, Lamia Chaari Fourati, and Abdessalam Chouaya. 2017. Internet of Things in Industry 4.0 Case Study: Fluid Distribution Monitoring System. In Computer Science & Information Technology (CS & IT). Academy & Industry Research Collaboration Center (AIRCC), 01--11.
[2]
Buke Ao, Yongcai Wang, Lu Yu, Richard R. Brooks, and S. S. Iyengar. 2016. On Precision Bound of Distributed Fault-Tolerant Sensor Fusion Algorithms. ACM Comput. Surv. 49, 1 (2016), 5:1--5:23.
[3]
Chinadaily. {n. d.}. Baotou Iron and Steel Group (Baotou Steel). ({n. d.}). http: //www.chinadaily.com.cn/business/2006-11/15/content_734141.htm
[4]
Mariusz Cieslak. 2008. Life cycle costs of pumping stations. World Pumps 2008, 505 (Oct. 2008), 30--33.
[5]
Haoran Feng, Yongcai Wang, and Jiajun Zhu. 2018. Multi-kernel Learning based Autonomous Fault Diagnosis for Centrifugal Pumps. The 2018 International Conference on Control, Automation and Information Sciences (2018).
[6]
Mohamed Fourati, Lamia Chaari Fourati, and Abdessalam Chouaya. 2017. Internet of Things in Industry 4.0 Case Study: Fluid Distribution Monitoring System.
[7]
Nien-Sheng Hsu, Chien-Lin Huang, and Chih-Chiang Wei. 2013. Intelligent real-time operation of a pumping station for an urban drainage system. Journal of Hydrology 489 (May 2013), 85--97.
[8]
M. Koor, A. Vassiljev, and T. Koppel. 2016. Optimization of pump efficiencies with different pumps characteristics working in parallel mode. Advances in Engineering Software 101 (Nov. 2016), 69--76.
[9]
Zhixian Lei, Xuehan Ye, Yongcai Wang, Deying Li, and Jia Xu. 2017. Efficient Online Model Adaptation by Incremental Simplex Tableau. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA. 2161--2167. http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14343
[10]
Stefano Mambretti and Enrico Orsi. 2016. Optimizing Pump Operations in Water Supply Networks Through Genetic Algorithms. Journal of American Water Works Association 108, 2 (Feb. 2016), E119-E125.
[11]
Miguel A. Moreno, Pedro A. Carriĺőn, Patricio Planells, Josĺę F. Ortega, and Josĺę M. Tarjuelo. 2007. Measurement and improvement of the energy efficiency at pumping stations. Biosystems Engineering 98, 4 (Dec. 2007), 479--486.
[12]
W. S. Ngueya, J. Mellier, S. Ricard, J. Portal, and H. Aziza. 2017. Power efficiency optimization of charge pumps in embedded low voltage NOR flash memory. In 2017 IEEE Nordic Circuits and Systems Conference (NORCAS): NORCHIP and International Symposium of System-on-Chip (SoC). 1--5.
[13]
Yongcai Wang, Haoran Feng, and Xiangyu Xi. 2017. Monitoring and autonomous control of Beijing Subway HVAC system for energy sustainability. Energy for Sustainable Development 39 (2017), 1--12.
[14]
M Zarei, Ayoub Mohammadian, and Rohollah Ghasemi. 2016. Internet of things in industries: A survey for sustainable development. 10 (Jan. 2016), 419--442.

Cited By

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  • (2024)Prediction Model for Safe Operation of Pumping Stations Optimized by the Sparrow Search Algorithm and BP Neural NetworkAdvances in Civil Engineering10.1155/2024/53589152024(1-12)Online publication date: 22-Jan-2024
  • (2024)Numerical and experimental investigation on vortex control and sedimentation suppression in a Y-shaped diversion channel with circular inlet tanksEngineering Applications of Computational Fluid Mechanics10.1080/19942060.2024.238029518:1Online publication date: 25-Jul-2024
  • (2022)Perspectives on the Advancement of Industry 4.0 Technologies Applied to Water Pumping Systems: Trends in Building PumpsEnergies10.3390/en1509331915:9(3319)Online publication date: 2-May-2022
  • Show More Cited By

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  1. Internet of Thing System to Extract Hierarchical Healthy and Efficiency Information for Pump Station Optimization

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      cover image ACM Other conferences
      BDIOT '18: Proceedings of the 2018 2nd International Conference on Big Data and Internet of Things
      October 2018
      217 pages
      ISBN:9781450365192
      DOI:10.1145/3289430
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      • Deakin University

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      Published: 24 October 2018

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      Author Tags

      1. Cyber-Pysical System
      2. Intelligent
      3. Internet of Things
      4. Pump Station
      5. Sustainability

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      Cited By

      View all
      • (2024)Prediction Model for Safe Operation of Pumping Stations Optimized by the Sparrow Search Algorithm and BP Neural NetworkAdvances in Civil Engineering10.1155/2024/53589152024(1-12)Online publication date: 22-Jan-2024
      • (2024)Numerical and experimental investigation on vortex control and sedimentation suppression in a Y-shaped diversion channel with circular inlet tanksEngineering Applications of Computational Fluid Mechanics10.1080/19942060.2024.238029518:1Online publication date: 25-Jul-2024
      • (2022)Perspectives on the Advancement of Industry 4.0 Technologies Applied to Water Pumping Systems: Trends in Building PumpsEnergies10.3390/en1509331915:9(3319)Online publication date: 2-May-2022
      • (2021)Implementation of Universal Health Management and Monitoring System in Resource-Constrained Environment Based on Internet of ThingsIEEE Access10.1109/ACCESS.2021.31019099(138744-138752)Online publication date: 2021

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