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Although it has been proved that kernel PCA is superior to linear PCA for fault detection, the fault identification method theoretically derived from the kernel PCA has not been found anywhere.
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Some recommendations for the fastest detection of the fault are given.
Four different ANN networks are designed for detection of the fault, fault section identification, classification of fault and location of fault in time domain.
The system had an error detection function and the fault detection system was not affected by formation factors.
This paper focuses on the derivation of a Fault Detection and Identification (FDI) filter for the detection of the faults that might occur during the operation of the actuator built in the suspension system.
Two distinct sets of fault indicators are determined, one for fault detection, the other one for fault isolation.
By using a general observer-based fault detection filter as a residual generator, the fault detection problem is described as a filter design problem.
The experimental results show that the fault detection probability and the fault detection speed are improved significantly, compared with the previous approaches.
A rigorous analysis of the detectability properties of the proposed fault detection scheme is also given, which includes the fault detectability condition and the fault detection time.
The fault detection algorithm can detect the presence of a fault within one power cycle.
However, in many practical cases, the fault detection systems have feedback control, that is, the fault detection system is usually of closed-loop type, and if the fault detection systems are designed separately from the control algorithms, faults may be hidden by control actions and the early detection of faults is clearly more difficult, especially low frequency faults [8 15].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com