Helicopter Hydraulic Pump Condition Monitoring Using Neural Net Analysis of the Vibration Signature BF Goodrich Technology Integration

Format:

Conference/Event

Author/Creator:

Succi, George P., author.

Conference Name:

Aerospace Atlantic Conference & Exposition (1996-05-01 : Dayton, Ohio, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 1996

Summary:

We apply artificial neural networks to helicopter hydraulic pump condition monitoring. Several neural net models are used to perform pattern classification on the vibration measurements. Various pump conditions are examined using data from accelerometers in different places on the pump. The fundamental pump frequencies and its harmonics are used as input features to two neural net models: (1) a multi-layer neural net using back-propagation and (2) a Kohonen's feature map. Both neural net models have the ability to distinguish between pumps with different flow rates and mechanical conditions. A fundamental result is that the vibration signature can be used to classify pump condition

Notes:

Vendor supplied data

Publisher Number:

961307

Access Restriction:

Restricted for use by site license