Browse Publications Technical Papers 2009-01-3164

Equipment Condition Monitoring and Prognostic Methods for Single Variable Systems 2009-01-3164

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.


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