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The Diagnostics and Prognostics (DnP) group maintains a laboratory to support the research of the prognostic techniques. Specifically, we are using the lab to understand some of the basic faults of the components to better model the damage they are incurring. We are also using the lab to age components and to generate data sets to test and ultimately support validation of the prognostic techniques.


The equipment directly available to the Diagnostics and Prognostics (DnP) group encompasses a 0.7m3 environmental chamber that allows the control of temperature (-60oC to 170oC), altitude (sea level to 30,000m), and humidity. Also available is a shaker that can accommodate small test articles (<1 kg) such as small wiring harnesses and computer boards. Several programmable loads, waveform generators, power supplies, oscilloscopes, data acquisition cards allow the automated aging of components and automated data collection. Electrochemical impedance spectroscopy equipment allows the probing of battery cells. A scanning electron microscope will be used in conjunction with sectioning equipment to perform forensic analysis of semiconductor devices.


Part of the Electronics Lab

Aging platforms have been designed or are underway to age batteries, MOSFETs and actuators.

electronics setup

Electronics Setup

battery chamber

Insightful View of the Environmental Chamber

Several demo stations allow the demonstration of the technology developed. These include:

  • The prognostics algorithms station that showcases different prognostic algorithms. The algorithms are run in real-time with hardware in the loop. As proof of concept, batteries at different degrees of aging were chosen as the test articles.
  • An electronics station that illustrates the damage characteristics of electronics components.
  • An actuator health management station that showcases the simulated actuator model and the vibrations that the nut experiences.
  • A controller reconfiguration station that illustrates how information about future damage can be utilized to mitigate damage and maximize mission objectives. The simulation uses a simple model for a pressure fed, monopropellant propulsion system for a small space flight vehicle.

actuator test stand

Electro-Mechanical Actuator Test Stand

Electro-mechanical actuator (EMA) test stand has been designed and built in collaboration with Impact Technologies. It will be used in experiments studying diagnostic and prognostic methods for ball-screw jams, spalling, abnormal wear, backlash, as well as electronics and power failures. Dynamic load for the test actuator is provided by a powerful Moog 886 load EMA that can produce up to 5 metric tons of opposing force. The control system of the stand will allow custom load profiles and long-term, endurance testing. Instrumentation includes a load cell, accelerometers, high-precision position sensors, and temperature sensors. The data acquisition system allows recording of data samples with frequency of up to 64 kHz. The flexible design of the stand accommodates test actuators of various sizes and configurations.

The test stand has become operational in September 2008.

This test bed is meant to provide a realistic development environment for future experiments in electro-mechanical actuator prognostics on manned and unmanned aircraft (such as NASA DFRC F-18 and NASA LaRC AirStar UAVs). It has been constructed from a wing section of a surplus Boeing 727 airliner. The section contains segments of the aileron, the aileron trim tab, and the leading edge flap. The original hydraulic aileron actuator has been removed and replaced with a Moog 883-023 electro-mechanical actuator and T200 controller. The leading edge flap and aileron trim segments will be utilized for future experiments.

The next steps in development of this test bed include:

  • Addition of variable dynamic load system for the aileron, to simulate aerodynamic loads
  • Addition of a more sophisticated control and data acquisition system
  • Installation of a mechanical adapter between the actuator and the aileron to simulate backlash and facilitate development of mitigation algorithms


Boeing 727 Aileron Wing Section Test Bed

adapt lab

Electrical Power System testbed in the ADAPT lab

The Electrical Power System testbed in the ADAPT lab provides: (i) a standard testbed for evaluating diagnostic algorithms and software; (ii) a capability for controlled insertion of faults, giving repeatable failure scenarios; and (iii) a mechanism for maturing and transitioning diagnostic technologies onto manned and unmanned vehicles.

The EPS functions of the testbed are as follows: For power generation, the testbed currently uses utility power. For power storage, it contains 2 sets of 24 VDC 100 Amp-hr sealed lead acid batteries and 1 24 VDC 50 Amp-hr battery. Each battery set comprises two 12 VDC batteries connected in series. Power distribution is aided by electromechanical relays and two load banks with six AC and two DC outputs; there are also several circuit breakers. At the present time, EPS loads include pumps, fans, and light bulbs. There are sensors of several types, specifically for measuring voltage, current, relay position, temperature, light, and liquid flow. Control and monitoring of the EPS takes place through programmable automation controllers from National Instruments. With the sensors included, the testbed contains a few hundred components and is representative of EPSs used in aerospace.


Group Lead

Chris Teubert

Deputy Group Lead

Wendy Okolo

SHARP Lab Operations Manager

George Gorospe

Group Members

Edward Balaban
Portia Banerjee
Matteo Corbetta
Katelyn Jarvis
Chetan Kulkarni
David Nishikawa
Molly O'Connor
Adam Sweet
Jason Watkins


Auburn University
Clarkson University
Georgia Tech
Global Technology
Idaho National Lab
Impact Technologies
Iowa State University
Montana Tech
Penn State ARL
Qualtech Systems, Inc.
Scientific Monitoring, Inc.
Sentient Corporation
Stanford University
Syracuse University
University of Connecticut
University of Maryland
Vanderbilt University


Brian Bole
Chris Bond
Jose Celaya
Jonny da Silva
Matthew Daigle
David Garcia
Kai Goebel
Tolga Kurtoglu
Peter Liu
Ole Mengshoel
Sriram Narasimhan
Scott Poll
Elinirina Robinson
Indranil Roychoudhury
Bhaskar Saha
Sankalita Saha
Shankar Sankararaman
Abhinav Saxena
Greg Sonnenfeld

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