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This paper presents a functional observer based fault detection method.
A reduced order unknown input observer based fault detection method is proposed.
This paper proposes an operator based fault detection method for an actuator fault of an aluminum plate thermal process with input constraints.
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Fuzzy model based fault detection methods are elaborated envisaging fault tolerant control.
Current data-driven based fault detection methods for hydraulic pump pay more attentions to not only linear characteristics but also nonlinear ones.
As the rate of change of voltage (ROCOV) based fault detection methods [9, 11] applied for detection of transmission line and bus faults demands both line side voltage and bus side voltages, no additional sensors are necessary.
Although communication based fault detection schemes such as current differential fault detection [13] and energy based fault detection methods [14, 15] are superior in terms of fault discrimination, any fault detection scheme which includes communication is not a likely to be satisfactory for primary protection of MT-HVDC grids as communication delays may not be tolerated.
In this study, a non-Gaussian pattern matching based fault detection and diagnosis method is developed and applied to monitor cryogenic air separation process.
Using a back-propagation neural network, a model-based fault detection method is employed to detect the PEMFC current fault type (flooding, membrane drying or normal).
An event-based fault detection method is applied to fault propagation analysis validation.
In some applications, white noise produces low quality output data for the subspace-based fault detection method.
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