Diagnostic by Fault Tree and Petri Nets of a Robotic Machining Cell

Journal article

Z Mehar, R Noureddine, F Noureddine
Algerian Journal of Research and Technology (AJRT), vol. 6, 2022, pp. 10-18

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APA Click to copy
Mehar, Z., Noureddine, R., & Noureddine, F. (2022). Diagnostic by Fault Tree and Petri Nets of a Robotic Machining Cell. Algerian Journal of Research and Technology (AJRT), 6, 10–18.

Chicago/Turabian Click to copy
Mehar, Z, R Noureddine, and F Noureddine. “Diagnostic by Fault Tree and Petri Nets of a Robotic Machining Cell.” Algerian Journal of Research and Technology (AJRT) 6 (2022): 10–18.

MLA Click to copy
Mehar, Z., et al. “Diagnostic by Fault Tree and Petri Nets of a Robotic Machining Cell.” Algerian Journal of Research and Technology (AJRT), vol. 6, 2022, pp. 10–18.

BibTeX Click to copy

@article{mehar2022a,
  title = {Diagnostic by Fault Tree and Petri Nets of a Robotic Machining Cell},
  year = {2022},
  journal = {Algerian Journal of Research and Technology (AJRT)},
  pages = {10-18},
  volume = {6},
  author = {Mehar, Z and Noureddine, R and Noureddine, F}
}

Abstract

The objective of this work is to propose a diagnostic technical method for robot cell machining. The developed approach is based on a hybrid diagnostic FT-PN (Fault Tree - Petri Nets). This technique consists of the Petri Nets implementation in the LabView environment (Laboratory Virtual Instrument Engineering Workbench), based on the knowledge of the Fault Tree of the robot cell. The simulations and results are obtained from the state of the operating system without and with fault are presented and discussed.

Keywords:

Diagnostic, Robotisation, FT, PN, LabView.