Crankshaft high cycle bending fatigue test method based on the combined extended Kalman filtering algorithm and...

Area of Science:

• Mechanical Engineering
• Materials Science
• Reliability Engineering

Background:

• Crankshafts are critical components in many mechanical systems.
• Accelerated fatigue testing is essential for efficient component evaluation.
• Predicting remaining fatigue life is crucial for ensuring component reliability.

Purpose of the Study:

• To develop an accelerated bending fatigue test method for crankshafts.
• To integrate the extended Kalman filtering (EKF) algorithm with failure criterion parameters.
• To reduce the overall testing duration without compromising key fatigue property analysis.

Main Methods:

• Proposed an accelerated bending fatigue test method for crankshafts.
• Utilized the extended Kalman filtering (EKF) algorithm for remaining high cycle fatigue life prediction.
• Selected intrinsic frequency and fatigue crack depth as failure criterion parameters.
• Employed fracture mechanics principles and test regulations.

Main Results:

• The proposed method significantly reduced test duration.
• Fatigue crack depth proved more suitable than intrinsic frequency as a failure criterion.
• Key analysis parameters were not adversely affected by the accelerated testing.

Conclusions:

• The developed accelerated fatigue test method offers a more efficient approach to crankshaft analysis.
• Fatigue crack depth is a more effective failure criterion for enhanced results.
• Findings provide theoretical guidance for crankshaft design and manufacturing processes.