Development of Diagnostic and Prognostic Technologies for Aerospace Health Management Applications

Abstract

Effective aerospace health management integrates component subsystem and system level health monitoring strategies, consisting of anomaly/diagnostic/prognostic technologies, with an integrated modeling architecture that addresses failure mode mitigation and life cycle costs. Included within such health management systems will be various failure mode diagnostic and prognostic (DIP) approaches ranging from generic signal processing and experience-based algorithms to the more complex knowledge and model-based techniques. While signal processing and experienced-based approaches to DIP have proven effective in many applications, knowledge and model-based strategies can provide further improvements and are not necessarily more costly to develop or maintain. This paper will describe some generic prognostic and health management technical approaches to confidently diagnose the presence of failure modes or prognose a distribution on remaining time to failure. Specific examples of DIP strategies are presented herein that address valves, hot section lifting and performance degradation of an Auxiliary Power Unit (APU) system. In addition, a model is presented for a Power Take Off (PTO) shaft and AMAD snout bearing.

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Document Details

Document Type
Technical Report
Publication Date
Apr 05, 2001
Accession Number
ADP013498

Entities

People

  • Emmanuel O. Nwadiogbu
  • George Bloor
  • Gregory J. Kacprzynski
  • Michael J. Roemer

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircraft Equipment
  • Aircrafts
  • Algorithms
  • Auxiliary Power Units
  • Computing System Architectures
  • Data Mining
  • Detection
  • Detectors
  • Failure Mode And Effect Analysis
  • Fighter Aircraft
  • Gas Turbines
  • Information Science
  • Neural Networks
  • Probability
  • Reliability
  • Signal Processing
  • Turbines

Fields of Study

  • Engineering

Readers

  • Distributed Systems and Data Platform Development
  • Fault Tolerant Diagnosis of Black and White Balloon Isolation Tests Using ¥.
  • Software Engineering.

Technology Areas

  • Space