Multi-mode fault dataset for aviation piston pump based on standard test procedure.

Area of Science:

• Aerospace Engineering
• Mechanical Engineering
• Condition Monitoring

Background:

• Aviation piston pumps are critical for hydraulic and fuel systems, operating under variable speeds and loads.
• Accurate fault diagnosis is essential for ensuring aircraft safety and operational reliability.
• Existing diagnostic methods face challenges under diverse working conditions.

Purpose of the Study:

• To design a standardized test procedure for aviation piston pumps.
• To create a comprehensive dataset for fault diagnosis research.
• To facilitate the development of advanced health evaluation methods.

Main Methods:

• Development of a standardized testing protocol for piston pumps.
• Collection of multi-signal data (pressure, flow rate, temperature, vibration).
• Inclusion of data under normal and three specific fault conditions (servo piston wear, regulation valve wear, swashplate bearing bush wear).

Main Results:

• A feasible standardized test procedure was successfully designed.
• A novel dataset containing critical operational signals was established.
• The dataset covers normal and common fault scenarios for validation.

Conclusions:

• The developed dataset and test procedure are valuable resources for the research community.
• This work supports the advancement of fault diagnosis and health monitoring for aviation piston pumps.
• Enables validation of new diagnostic algorithms under realistic operating conditions.