Fault diagnosis for wind turbine planetary ring gear via a meshing resonance based filtering algorithm

Area of Science:

• Mechanical Engineering
• Vibration Analysis
• Condition Monitoring

Background:

• Planetary gearboxes are critical components in many mechanical systems.
• Local fault detection in planetary gearboxes often relies on spectral analysis of vibration signals.
• Non-fault related phenomena can mimic ring gear fault signatures, complicating detection.

Purpose of the Study:

• To develop an improved method for detecting local faults in planetary gearbox ring gears.
• To address the challenge of distinguishing true ring gear faults from other signal interferences.
• To enhance the reliability of condition monitoring for planetary gearboxes.

Main Methods:

• A novel filtering algorithm is proposed, leveraging the meshing resonance phenomenon.
• The raw vibration signal is decomposed into various frequency bands and levels.
• A meshing index and MRgram are constructed to identify relevant resonance frequency bands.
• An optimal filter band is selected based on the MRgram for signal processing.

Main Results:

• The proposed algorithm effectively isolates the characteristic frequencies associated with ring gear faults.
• The filtering approach mitigates interference from non-fault related sources.
• Successful detection of local ring gear faults is demonstrated through envelope spectrum analysis of the filtered signal.

Conclusions:

• The developed filtering algorithm offers a robust strategy for planetary gearbox local fault detection.
• Utilizing meshing resonance analysis enhances the accuracy and reliability of ring gear fault diagnosis.
• This method contributes to improved condition monitoring and predictive maintenance of critical machinery.