We present a fault detection method called the gray-box. The term “gray-box” refers to the approach wherein a deterministic model of system, i.e., “white box,” is used to filter the data and generate a residual, while a stochastic model, i.e., “black-box” is used to describe the residual. The residual is described by a three-tier stochastic model. An auto-regressive process, and a time-delay feed-forward neural network describe the linear and nonlinear components of the residual, respectively. The last component, the noise, is characterized by its moments. Faults are detected by monitoring the parameters of the auto-regressive model, the weights of the neural network, and the moments of noise. This method is demonstrated on a simulated system of a gas turbine with time delay feedback actuator.
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September 2003
Technical Papers
Gray-Box Approach for Fault Detection of Dynamical Systems
Han G. Park,
Han G. Park
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA 91109
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Michail Zak
Michail Zak
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA 91109
Search for other works by this author on:
Han G. Park
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA 91109
Michail Zak
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA 91109
Contributed by the Dynamic Systems, Measurement, and Control Division of THE AMERICAN SOCIETY OF MECHANICAL ENGINEERS for publication in the ASME JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received by the ASME Dynamic Systems and Control Division January 18, 2001; final revision, March 24, 2003. Associate Editor: S. Sivashankar.
J. Dyn. Sys., Meas., Control. Sep 2003, 125(3): 451-454 (4 pages)
Published Online: September 18, 2003
Article history
Received:
January 18, 2001
Revised:
March 24, 2003
Online:
September 18, 2003
Citation
Park, H. G., and Zak, M. (September 18, 2003). "Gray-Box Approach for Fault Detection of Dynamical Systems ." ASME. J. Dyn. Sys., Meas., Control. September 2003; 125(3): 451–454. https://doi.org/10.1115/1.1589032
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