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Related Concept Videos

Bearings: Problem Solving01:24

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Understanding the calculations and concepts related to double-collar bearings is essential for engineers and designers to optimize the performance of these components in various applications. By analyzing the bearing under different conditions, one can ensure that it can withstand the forces and moments experienced during operation. This knowledge enables better decision-making when designing and selecting bearings for specific purposes and configurations. Consider a double-collar bearing with...
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Rolling Resistance: Problem Solving01:17

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Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
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Journal bearings are mechanical components that support and provide lateral stability to rotating shafts and axles. They are crucial in reducing friction, wear, and vibration in machinery such as engines, turbines, and pumps. The principle behind journal bearings is forming a thin lubricant film between the bearing surface and the rotating shaft, which minimizes direct contact and reduces frictional forces.
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When a solid cylinder rolls steadily on a rigid surface, the normal force applied by the surface on the cylinder is perpendicular to the tangent at the contact point. However, since no materials are entirely rigid, the surface's reaction to the cylinder involves a range of normal pressures.
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Fault Diagnosis Method for Rolling Bearings Based on Grey Relation Degree.

Yulin Mao1, Jianghui Xin1, Liguo Zang1,2

  • 1School of Automotive and Rail Transit, Nanjing Institute of Technology, Nanjing 211167, China.

Entropy (Basel, Switzerland)
|March 28, 2024
PubMed
Summary

This study introduces a novel fault diagnosis method for rolling bearings using grey relation degree analysis. The technique enhances accuracy in identifying bearing faults across their entire operational lifespan.

Keywords:
fault diagnosisgrey relational degreeminimum envelope entropyrolling bearingssubtraction-average-based optimizervariational mode decomposition

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Area of Science:

  • Mechanical Engineering
  • Signal Processing
  • Artificial Intelligence

Background:

  • Rolling bearings are critical components in machinery, and their failure can lead to significant downtime and costs.
  • Accurate fault diagnosis throughout the entire lifecycle of rolling bearings remains a challenging problem.
  • Existing methods often struggle with extracting subtle fault characteristics and maintaining high diagnostic accuracy.

Purpose of the Study:

  • To propose a robust fault diagnosis method for rolling bearings applicable throughout their full operational life.
  • To improve the accuracy and reliability of bearing fault detection and classification.
  • To provide a reference for advanced condition monitoring and predictive maintenance strategies.

Main Methods:

  • Optimization of Variational Mode Decomposition (VMD) parameters using a subtraction-average-based optimizer.
  • Decomposition of bearing vibration signals using optimized VMD and extraction of feature vectors from intrinsic mode functions (IMFs) based on minimum envelope entropy.
  • Calculation of a grey comprehensive relation degree by weighting grey proximity and similarity relation degrees based on standard distance entropy.

Main Results:

  • The proposed method achieved a diagnostic accuracy of 95.24% on the XJTU-SY dataset.
  • Demonstrated superior diagnostic performance compared to various existing algorithms.
  • Successfully diagnosed different fault states and degrees in rolling bearings.

Conclusions:

  • The grey relation degree-based fault diagnosis method offers a significant advancement in rolling bearing condition monitoring.
  • The approach effectively extracts fault characteristics and enhances diagnostic accuracy across the bearing's full life cycle.
  • This method provides a valuable tool for ensuring the reliability and longevity of mechanical systems.