Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

article · 2024

Modelling of Advanced Sensor based Distributed Control System for Real- Time Prediction and Minimization of Power Loss in Industrial Automation Systems

D. Sengeni, M. R. Mano Jemila, G.S. Krishna Priya, T. Santhana Krishnan, G. Rathinasabapathi, Sathish Kannan

Cited by 3Abstract and details only

Abstract

This research study analyses the integration of a Distributed Control System (DCS) to optimise the efficiency and reliability of industrial automation, with a special emphasis on reducing power loss. Leveraging real-time sensor data and machine learning models, including Decision Trees, Artificial Neural Networks, and Random Forests, the research provides a proactive strategy to anticipating and avoiding anomalous current and voltage patterns. The DCS, armed with predictive maintenance procedures, emerges as a solid framework for reducing energy usage, assuring system stability, and limiting possible quality losses. Evaluation using performance ratings and confusion matrices reveals the efficiency of the proposed system in properly recognising and correcting deviations from normal operating circumstances. The results contribute not only to the progress of distributed control systems in industrial automation but also provide a realistic approach to real-time monitoring and predictive maintenance, supporting sustainability and operational excellence in manufacturing settings. This study sets a platform for future initiatives seeking to construct intelligent, adaptable systems for increased industrial automation performance.

Cite this paper

APA 7

Sengeni, D., Jemila, M. R. M., Priya, G. K., Krishnan, T. S., Rathinasabapathi, G., & Kannan, S. (2024). Modelling of Advanced Sensor based Distributed Control System for Real- Time Prediction and Minimization of Power Loss in Industrial Automation Systems. https://doi.org/10.1109/icoeca62351.2024.00080

MLA 9

Sengeni, D., et al. “Modelling of Advanced Sensor based Distributed Control System for Real- Time Prediction and Minimization of Power Loss in Industrial Automation Systems.” 2024, pp. 413–19, https://doi.org/10.1109/icoeca62351.2024.00080.

Chicago

Sengeni, D., M. R. Mano Jemila, G.S. Krishna Priya, T. Santhana Krishnan, G. Rathinasabapathi, and Sathish Kannan. 2024. “Modelling of Advanced Sensor based Distributed Control System for Real- Time Prediction and Minimization of Power Loss in Industrial Automation Systems.” https://doi.org/10.1109/icoeca62351.2024.00080.

Harvard

Sengeni, D. et al. (2024) ‘Modelling of Advanced Sensor based Distributed Control System for Real- Time Prediction and Minimization of Power Loss in Industrial Automation Systems’. Available at: https://doi.org/10.1109/icoeca62351.2024.00080.

BibTeX
@article{sengeni2024modelling,
  title = {{Modelling of Advanced Sensor based Distributed Control System for Real- Time Prediction and Minimization of Power Loss in Industrial Automation Systems}},
  author = {Sengeni, D. and Jemila, M. R. Mano and Priya, G.S. Krishna and Krishnan, T. Santhana and Rathinasabapathi, G. and Kannan, Sathish},
  pages = {413--419},
  year = {2024},
  doi = {10.1109/icoeca62351.2024.00080}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers