Background/Introduction <p>Two-stage gear transmission systems are critical for power transfer in high-torque applications, but long-term heavy-load operation often leads to concurrent gear and bearing faults. Existing research focuses more on single faults, leaving multi-component coupling fault analysis insufficient.</p> Purpose <p>This study aims to explore the vibration characteristics and coupling mechanisms of gear tooth pitting and bearing raceway spalling, providing theoretical support for accurate fault diagnosis and operational safety protection.</p> Methods <p>A multi-degree-of-freedom dynamic model integrating multi-parameter excitation and coupling faults was established, validated with open-source experimental datasets. Multi-dimensional analysis methods including time domain, frequency domain, axis orbit, and phase diagram were used to extract fault features.</p> Results <p>Fault severity positively correlates with vibration intensity; the system exhibits complex chaotic motion under coupling faults, where bearing fault impulses tend to mask gear fault features. Outer raceway spalling causes stronger impacts than inner raceway spalling.</p> Conclusions <p>The established dynamic model effectively characterizes coupling fault behaviors, and the multi-dimensional analysis method enables reliable fault identification, laying a foundation for intelligent health monitoring systems of gear transmission systems.</p>

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Vibration Characteristics Analysis of multi-component Coupling Fault in Gear Transmission System

  • Shi Wang,
  • Xuan Li,
  • Yawen Wang

摘要

Background/Introduction

Two-stage gear transmission systems are critical for power transfer in high-torque applications, but long-term heavy-load operation often leads to concurrent gear and bearing faults. Existing research focuses more on single faults, leaving multi-component coupling fault analysis insufficient.

Purpose

This study aims to explore the vibration characteristics and coupling mechanisms of gear tooth pitting and bearing raceway spalling, providing theoretical support for accurate fault diagnosis and operational safety protection.

Methods

A multi-degree-of-freedom dynamic model integrating multi-parameter excitation and coupling faults was established, validated with open-source experimental datasets. Multi-dimensional analysis methods including time domain, frequency domain, axis orbit, and phase diagram were used to extract fault features.

Results

Fault severity positively correlates with vibration intensity; the system exhibits complex chaotic motion under coupling faults, where bearing fault impulses tend to mask gear fault features. Outer raceway spalling causes stronger impacts than inner raceway spalling.

Conclusions

The established dynamic model effectively characterizes coupling fault behaviors, and the multi-dimensional analysis method enables reliable fault identification, laying a foundation for intelligent health monitoring systems of gear transmission systems.