Helicopter Planet Gear Rim Crack Diagnosis and Trending Using Cepstrum Editing Enhanced with Deconvolution

Area of Science:

• Mechanical Engineering
• Vibration Analysis
• Condition Monitoring

Background:

• Gearbox failure is a major concern in aviation, particularly in helicopter transmissions.
• Detecting gear rim fatigue cracks via vibration analysis is complex due to signal interference.

Purpose of the Study:

• To develop an effective signal processing algorithm for isolating and enhancing gear rim crack features.
• To enable reliable trending of crack growth in planet gears within helicopter gearboxes.

Main Methods:

• The proposed algorithm utilizes cepstrum editing (liftering) on hunting-tooth synchronous averaged signals.
• Low-pass filtering and minimum entropy deconvolution (MED) are employed to enhance fault features.
• The method was validated using vibration data from a seeded crack propagation test in a helicopter planetary gearbox.

Main Results:

• The algorithm successfully isolated incipient fault features indicative of gear rim cracks.
• Reliable trending of crack progression throughout the test was achieved.
• The proposed method demonstrated superior performance compared to traditional signal processing techniques.

Conclusions:

• The developed algorithm provides an effectual solution for detecting and monitoring gear rim fatigue cracks in complex gearbox environments.
• This advancement offers improved condition monitoring capabilities for critical helicopter transmissions.