A new performance analysis method for rolling bearing based on the evidential reasoning rule considering perturbation

Area of Science:

• Mechanical Engineering
• Reliability Engineering

Background:

• Rolling bearings are critical components in rotating machinery, essential for industrial applications.
• Evaluating the performance and reliability of rolling bearings is vital due to operational interference issues.

Purpose of the Study:

• To propose a novel performance evaluation model for rolling bearings.
• To address interference problems in rolling bearings during operation.
• To enhance the reliability assessment of rolling bearings in complex environments.

Main Methods:

• Constructed an evaluation system using time and frequency domain characteristic indicators of bearing vibration signals.
• Unified indicator information into a belief structure, incorporating indicator reliability and weight within the evidential reasoning (ER) rule.
• Employed perturbation analysis to simulate complex working environments and analyze performance reliability, proposing a perturbation-considering model.

Main Results:

• Developed a performance reliability evaluation model for rolling bearings.
• Successfully verified the model's validity and reliability using whole-life open data sets.
• Demonstrated the model's effectiveness in analyzing rolling bearing performance under simulated complex conditions.

Conclusions:

• The proposed evidential reasoning-based model effectively evaluates rolling bearing performance and reliability.
• The inclusion of perturbation analysis enhances the model's applicability to real-world, complex industrial environments.
• The validated model provides a robust tool for ensuring the operational integrity of critical machinery components.