SBIR-STTR Award

Neural Network Based Expert System For ASTF Fault Diagnosis
Award last edited on: 9/5/2002

Sponsored Program
SBIR
Awarding Agency
DOD : AF
Total Award Amount
$48,349
Award Phase
1
Solicitation Topic Code
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Principal Investigator
Y C L Susan Wu

Company Information

Engineering Research & Consulting Inc (AKA: ERC)

4901 Corporate Drive Suite E
Huntsville, AL 35805
   (256) 430-3080
   klyles@erc-incorporated.com
   www.erc-incorporated.com
Location: Multiple
Congr. District: 05
County: Madison

Phase I

Contract Number: ----------
Start Date: 00/00/00    Completed: 00/00/00
Phase I year
1990
Phase I Amount
$48,349
Engineering Research And Consulting, Inc. (ERCI) proposes to develop a prototype neural network based expert system (connectionist expert system) for ASTF fault diagnosis. Neural networks are excellent for parameter estimation and recognizing patterns in signal data. The objective of this research is to design a neural network architecture to detect fault thus signifying and responding to an abnoral event. Once a successful architecture is designed, an expert system will be built using the resulting neural network output curve as a premise to a rule. The neural network based expert system can advise the engineer and/or be integrated to the Emergency Detection And Response (EDAR) function which is a part of the ASTF fault-tolerant control system. Phase I of this project will implement a prototype neural architecture using fault data generated by a simulator. The resultant network output curves will be used as rule premise for an expert system, where rule clauses will be recommendations to engineers and/or the EDAR for control of ASTF. Phase II of the project will extend the system from Phase I to build a connectionist expert system for ASTF fault diagnosis.

Phase II

Contract Number: ----------
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
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Phase II Amount
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