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- W3213385827 abstract "Detecting faults in systems is important, as the occurrence of faults may have drastic consequences. In this paper, complications with respect to analytical model-based fault detection algorithms using statistical techniques are investigated. Using a static problem in combination with Monte Carlo simulations and analytical properties of some test statistics, properties regarding hypothesis testing were investigated. Moreover, applying a Kalman filter based detection scheme in combination with discretised stochastic differential equations, simulations were done for a DC motor. It followed that there is a trade-off between the certainty that a fault is reliably detected, the probability of a false alarm and the speed of detection. Moreover, complications such as a dependency on both the sampling interval and the number of measurements per sample occurred. The dynamical case has many more complications to deal with than the static problem." @default.
- W3213385827 created "2021-11-22" @default.
- W3213385827 creator A5070828213 @default.
- W3213385827 date "2019-01-01" @default.
- W3213385827 modified "2023-09-27" @default.
- W3213385827 title "On the speed characteristics of fault detection algorithms in dynamical systems" @default.
- W3213385827 hasPublicationYear "2019" @default.
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