| Project Summary | Project Information |
|---|---|
|
For an updated project description, click on the following link for the Project Readiness Package. The use of Electro-Mechanical Actuators (EMA) in place of hydraulic actuators in aircraft applications has received significant attention in recent years due to their lack of supporting hardware, thereby reducing mass, volume, and maintenance. However, this benefit is not without risk. The failure modes associated with current EMAs can often occur without sufficient notice. For EMAs to be widely-utilized fault detection and failure prediction methodologies must be an integral part of the Health & Usage Monitoring System (HUMS). State-of-health prediction in engineering systems is a rapidly evolving field that has a strong application to flight actuation. The proposed project seeks to build on the success of recent health classification research concluded by a MOOG employee resulting in a RIT Master’s thesis in the spring of 2011. For this research an industrial grade EMA was installed in a test fixture with data acquisition and control capabilities. Tests were run with healthy and faulty bearings. The measurements were post-processed in a data-driven, Bayesian framework to accurately classify state-of-health. At the conclusion of this work the EMA and test rig were deconstructed. It is this, Moog controller and LVDT that has been offered for donation to be installed and commissioned at RIT for future flight actuator HUMS research projects.
|
Team Members
put team photo here
| Member | Role | Contact |
|---|---|---|
| Bradley Adriaansen | ME, Group Lead | bsa2780 |
| Joseph Mazzara | ME | jhm9927 |
| Brett Adams | ME | bca4153 |
| Joshua Cocos | EE | jnc1175 |
| Hussain Albandi | EE | hma6725 |
Table of Contents
| MSD I | MSD II |
|---|---|
Acknowledgements
- Viewing the latest revision
- Node updated 2012-05-30 08:14 by bsa2780