Bearing Dynamics Modeling Based on the Virtual State-Space and Hammerstein-Wiener Model

Area of Science:

• Mechanical Engineering
• Control Theory
• Signal Processing

Background:

• Rotating machinery transmission systems are critical in industrial applications.
• Assessing the health status of these systems, particularly bearings, is essential for preventing failures.
• Existing methods may lack the precision to capture dynamic degradation effectively.

Purpose of the Study:

• To develop a novel approach for assessing the health status of rotating machinery transmission systems.
• To analyze the dynamic degradation of bearings using a multi-dimensional modeling technique.
• To validate the proposed method's accuracy and effectiveness.

Main Methods:

• Generating multi-dimensional data through virtual states and virtual state-space.
• Applying Hammerstein-Wiener (HW) modeling from control theory to identify dynamic multi-dimensional models.
• Validating the model using four recognized databases with vibration sensor data.

Main Results:

• Achieved a modeling accuracy of 99% for multiple bearings under various conditions.
• Demonstrated the effectiveness of the dynamic modeling method through comparative analysis.
• Confirmed the approach's capability in evaluating transmission system health.

Conclusions:

• The proposed Hammerstein-Wiener modeling approach provides a novel and highly accurate method for assessing rotating machinery health.
• This technique offers a reliable reference for condition monitoring and predictive maintenance of transmission systems.
• The multi-dimensional modeling based on virtual states effectively captures dynamic bearing degradation.