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Equipment Condition Monitoring and Prognostic Methods for Single Variable Systems
Technical Paper
2009-01-3164
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
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
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1.
Normal feature prediction over different operating conditions
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Actual feature measurement and residual generation
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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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Authors
Topic
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.Also In
References
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