Powertrain Embedded Diagnostic and Predictive Capability for an Automotive Transmission

Abstract

This report documents the investigation of a vibration-based diagnostic approach developed for automotive transmissions. Data was recorded throughout three durability tests that were conducted by the transmission OEM. Rebuilt transmissions were operated around the clock under the most demanding speed and load set-points until critical gear or bearing failures resulted in loss of operability. The analysis results indicate that an embedded diagnostic and predictive capability can be implemented for military ground vehicle transmissions using vibration-based techniques. The results also specifically show an early indication of a fault condition is possible three weeks before failure for the test transmission. A technique for detecting solenoid faults using only the existing control signals rather than response measurements comparison that does not require the installation of additional sensors was also developed through this effort and will be discussed. This paper highlights the diagnostics techniques for the bearing and solenoid faults. On-platform testing is suggested for technique validation and future development of these initial findings.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2012
Accession Number
ADA566775

Entities

People

  • Jason Hines
  • Jeffrey Banks
  • Jim Bechtel
  • Jonathan Bednar
  • Larry Marino
  • Mitchell Lebold
  • Scott Pflumm

Organizations

  • Pennsylvania State University

Tags

Communities of Interest

  • Biomedical
  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Bearing Cages
  • Data Analysis
  • Data Fusion
  • Data Science
  • Degradation
  • Detection
  • Detectors
  • Engineering
  • Failure Mode And Effect Analysis
  • Frequency
  • Frequency Domain
  • Ground Vehicles
  • Information Science
  • Solenoids
  • Statistical Analysis
  • Systems Engineering

Fields of Study

  • Engineering

Readers

  • Aerospace Test and Evaluation
  • Electrical Engineering
  • Parallel and Distributed Computing.