Condition Based Maintenance for Light Trucks

Abstract

Army ground vehicles often operate in extremely severe environmental and battlefield conditions. There are challenges for the reliability of the military ground vehicle fleet, which need to be addressed. Condition Based Maintenance (CBM) allows maintenance to be performed based on evidence of need provided by reliability modeling and/or other enabling technologies, thus reducing maintenance costs and increasing vehicle availability. The architecture of the Intelligent Vehicle Health Management System (IVHMS) for light trucks is presented. A fuzzy model is developed to diagnose the axle fatigue of the vehicle. The extraction of the fuzzy rules is based upon expert knowledge and a linear damage model. Training data will be used to modify the membership functions and the fuzzy If-Then rules to improve the quality of the fuzzy model for fault diagnostics. The improvement of the fuzzy model will be carried out using re-clustering operation and membership function optimization.

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Document Details

Document Type
Technical Report
Publication Date
Oct 10, 2010
Accession Number
ADA573623

Entities

People

  • Bradley Bazuin
  • Janos Grantner
  • Jumana Al-shawawreh
  • Liang Dong
  • Matthew P. Castanier
  • Shabbir Hussain

Organizations

  • United States Army Tank Automotive Research, Development and Engineering Center

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Autonomous Vehicles
  • Clustering
  • Computers
  • Condition Based Maintenance
  • Data Storage Systems
  • Engineering
  • Extraction
  • Failure Mode And Effect Analysis
  • Materials
  • Measurement
  • Multiple Input Multiple Output
  • Network Topology
  • Optimization
  • Reliability
  • Training
  • Vehicles

Fields of Study

  • Engineering

Readers

  • Artificial Intelligence
  • Logistics and Supply Chain Management.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.