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Operation of the Collaborative Composite Manufacturing CCM System
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Research on rapier loom fault system based on cloud-side collaboration.

Yanjun Xiao1, Kuan Wang1, Weiling Liu1

  • 1College of Mechanical Engineering, Hebei University of Technology, Tianjin, China.

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|December 31, 2021
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Summary

This study introduces a novel fault diagnosis method for rapier weaving machines, combining edge expert systems with cloud-based analysis. This approach effectively identifies and addresses electrical control system failures, improving production efficiency.

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Area of Science:

  • Textile Engineering
  • Electrical Engineering
  • Computer Science

Background:

  • Rapier weaving machine electrical control systems are prone to operational disturbances and failures, impacting production.
  • Existing fault diagnosis systems have limitations due to the specific process and electrical characteristics of rapier looms.
  • A need exists for improved fault diagnosis to enhance the reliability and efficiency of rapier weaving operations.

Purpose of the Study:

  • To conduct an in-depth study of rapier loom fault diagnosis systems.
  • To propose an improved fault diagnosis method for rapier loom electrical control systems.
  • To enhance the reliability and reduce downtime in rapier weaving production.

Main Methods:

  • Developed a hybrid fault diagnosis method integrating an edge expert system and cloud-based rough set and Bayesian network.
  • Classified rapier loom electrical faults into common and other faults based on occurrence frequency.
  • Implemented an edge expert system for diagnosing common faults and a cloud-based system for complex fault analysis.

Main Results:

  • The edge expert system effectively diagnoses common rapier loom faults, reducing cloud computing load.
  • Cloud-based algorithms successfully diagnose other, less frequent faults.
  • On-site operation and remote monitoring validated the effectiveness of the proposed fault diagnosis system.

Conclusions:

  • The proposed hybrid fault diagnosis method significantly improves the accuracy and efficiency of rapier loom fault detection.
  • This approach addresses the limitations of existing systems, offering a practical solution for the textile industry.
  • The study provides a valuable technical framework for developing advanced fault diagnosis systems for industrial machinery.