Statistical Approach to Fault Detection of Gears

Abstract

The cost associated with machinery maintenance is a major portion of operating expenses. Vibration analysis, used as a method of monitoring the condition of machinery, provides a means to identify machinery faults before significant levels of damage occur. The results of research using statistical parameters of the vibration signal produced by machinery is presented. The statistical parameters investigated included the mean, mean square, variance, and coefficients of skewness and kurtosis. These values are compared with results of spectrum analysis techniques similar to methods used by the United States Navy in machinery programs. The investigation focuses on the use of band limited statistical parameters used as a fault detection technique that permits machinery operation to be categorized as 'satisfactory' or 'unsatisfactory.' Keywords: Theses, Statistical analysis, Gears, Machinery vibration monitoring, Fault detection, Machinery condition monitoring.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1989
Accession Number
ADA225386

Entities

People

  • J. D. Robinson

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Computer Programming
  • Computers
  • Detection
  • Engineering
  • Frequency
  • Frequency Bands
  • Gear Noise
  • Gears
  • Maintenance Personnel
  • Measurement
  • Mechanical Engineering
  • Preventive Maintenance
  • Probability
  • Probability Density Functions
  • Resonant Frequency
  • Test Equipment
  • United States

Fields of Study

  • Engineering

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