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Research Article | Open Access |

The Performance of the Bond Graph Approach for Diagnosing Electrical Systems

Author 1: Dhia Mzoughi Author 2: Abderrahmene Sallami Author 3: Abdelkader Mami
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 8, No. 7 · Published 2017

DOI: https://doi.org/10.14569/IJACSA.2017.080711

Abstract

The increasing complexity of automated industrial systems, the constraints of competitiveness in terms of cost of production and facility security have mobilized in the last years a large community of researchers to improve the monitoring and the diagnosis of this type of processes. This work proposes a reliable and efficient method for the diagnosis of an electrical system. The improvement of the reliability of the systems depends essentially on the algorithms of fault detection and isolation. The developed method is based on the use of analytical redundancy relations allowing the detection and isolation of faults which occur in the various elements of the system using a structural and causal analysis. In this context, the bond graph appears as an interesting approach since it models physical systems element by element which facilitates the detection and location of faults. The simulation of the system is performed through 20-sim software dedicated to the bond graph applications.

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How to Cite this Article

Mzoughi, D., Sallami, A., & Mami, A. (2017). The Performance of the Bond Graph Approach for Diagnosing Electrical Systems. International Journal of Advanced Computer Science and Applications, 8(7). https://doi.org/10.14569/IJACSA.2017.080711

Mzoughi, Dhia, et al.. "The Performance of the Bond Graph Approach for Diagnosing Electrical Systems." International Journal of Advanced Computer Science and Applications, vol. 8, no. 7, 2017, https://doi.org/10.14569/IJACSA.2017.080711.

@article{Mzoughi2017,
  title     = {The Performance of the Bond Graph Approach for Diagnosing Electrical Systems},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {7},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Dhia Mzoughi and Abderrahmene Sallami and Abdelkader Mami},
  doi       = {10.14569/IJACSA.2017.080711},
  url       = {https://doi.org/10.14569/IJACSA.2017.080711}
}

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