Equipment Condition Monitoring and Prognostic Methods for Single Variable Systems

2009-01-3164

11/10/2009

Event
Aerospace Technology Conference and Exposition
Authors Abstract
Content
This paper introduces empirical modeling techniques for process and equipment monitoring, fault detection and diagnostics, and prognostics. The paper first provides a brief background and an overview of the theoretical foundations and presents a new method for applying these methods to systems which only have one useful measured variable. A case study is then presented for the application of the method to an aircraft generator that includes
  • 1.
    Normal feature prediction over different operating conditions
  • 2.
    Actual feature measurement and residual generation
  • 3.
    Fault detection, identification, and quantification
Application of the proposed single variable monitoring system to the simulated aircraft generator data resulted in fault diagnosis accuracy of 96.3%, only one misdiagnosed case in 27, for the types and severities of faults considered. Future work in developing a prognostic model for a single-variable system will be outlined.
Meta TagsDetails
DOI
https://doi.org/10.4271/2009-01-3164
Pages
5
Citation
Hines, J., Coble, J., and Bailey, B., "Equipment Condition Monitoring and Prognostic Methods for Single Variable Systems," SAE Technical Paper 2009-01-3164, 2009, https://doi.org/10.4271/2009-01-3164.
Additional Details
Publisher
Published
Nov 10, 2009
Product Code
2009-01-3164
Content Type
Technical Paper
Language
English