A Method to Predict Compressor Stall in the TF34-100 Turbofan Engine Utilizing Real-Time Performance Data

Abstract

The Air Force current operations continue to undergo significant changes compelled by decreasing fiscal appropriations, aging aircraft, and personnel drawdown. The Air Force must effectively improve current maintenance operations in part to deal with these challenges. This study will explore the area of the A-10 aircraft fleet's TF34-100 high-pass turbo-fan engine sensor data to seek its deterioration modelling and prognostics capability. In futurity this will allow for achievement of greater confidence in predicting the compressor stall which leads to engine performance deterioration and a costly repair in maintenance. By utilizing an innovative method to forecast the probability of compressor stall, according to individual engine sensor data which has recently become available, it will be possible to achieve significant benefits in both maintenance planning and mission scheduling (which will greatly reduce the associated costs of maintenance servicing).

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2015
Accession Number
ADA621762

Entities

People

  • Shuxiang Li
  • Trevor G. Jones

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Human Systems
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Business Administration
  • Data Analysis
  • Department Of Defense
  • Engineering
  • Governments
  • Information Science
  • Maintenance
  • Preventive Maintenance
  • Probability
  • Reliability
  • Standards
  • Students
  • Systems Engineering
  • Turbofan Engines
  • United States
  • United States Government

Fields of Study

  • Engineering

Readers

  • Aerospace Engineering
  • Instructional Design and Training Evaluation.
  • Maritime Combat Support and Expeditionary Logistics.