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Damage Caused by Material Defects of Carbon Composites Used on Various Types of Railway Pantographs.

Materials (Basel, Switzerland)·2023
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A Method of Predicting Wear and Damage of Pantograph Sliding Strips Based on Artificial Neural Networks.

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A Study on the Effect of Adhesive Cavities on the Scuffing Initiation in a Sliding Contact.

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Pantograph Sliding Strips Failure-Reliability Assessment and Damage Reduction Method Based on Decision Tree Model.

Małgorzata Kuźnar1, Augustyn Lorenc1, Grzegorz Kaczor1

  • 1Department of Rail Vehicles and Transport, Faculty of Mechanical Engineering, Cracow University of Technology, 31-155 Kracow, Poland.

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Summary

Predicting pantograph sliding strip failures is crucial for railway operations. This study developed a decision tree model that can reduce failures by up to 50%, preventing transport disruptions.

Keywords:
AI methodsartificial neural networkdamage preventionfailure distribution modelmachine learningpantograph stripreliability assessment

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Area of Science:

  • Railway Engineering
  • Materials Science
  • Predictive Maintenance

Background:

  • Pantograph and sliding strip damage can lead to railway line blockages.
  • Predicting pantograph failures is vital for railway carriers and researchers to ensure transport chain continuity.

Purpose of the Study:

  • To develop and evaluate a sliding strip failure prediction method.
  • To minimize disruptions in the railway transport chain through predictive maintenance.

Main Methods:

  • Machine learning methods including complex, medium, and simple decision trees were tested.
  • Non-destructive degradation analysis and wear measurements of pantograph strips were performed.
  • A failure distribution model was developed based on wear measurements and critical wear values.

Main Results:

  • The decision tree model demonstrated the ability to categorize technical conditions effectively.
  • The presented predictive model can potentially reduce sliding strip failures by up to 50%.
  • Operational data from a major Polish railway carrier was utilized for analysis.

Conclusions:

  • The developed method provides a robust approach to predicting pantograph sliding strip failures.
  • The findings can inform the development of preventive maintenance strategies for pantographs.
  • Reliability models can be extended with cost and repair time parameters for operational and maintenance cost estimation.