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In experiments, the proposed method has been applied in fault diagnosis for rotatory bearing, while SWKC-GS has been compared not only with traditional clustering methods, but also with SVM and neural network, for known fault diagnosis.
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In addition, the proposed method has also been applied in unknown fault diagnosis.
The NP criterion has also been applied in some other topics: watermarking[9, 10], fault-induced dips detection[11], detection in sensor networks[12], disease diagnosis[13, 14], biometric[15], or gravitational waves detection[16].
Autonomic architectures have been applied in industry systems to find early indications of failures and to investigate fault causes.
Transient signal analysis (TSA) has been proven an effective tool for motor bearing fault diagnosis, but has yet to be applied in processing bearing fault signals with variable rotating speed.
Moreover, the proposed method is applied in the intelligent fault diagnosis of locomotive roller bearings, which proves the capability of detecting multiple faults including complex compound faults and different severe degrees with the same fault.
Shared lightpath protection is applied in the second-level fault tolerance design to reduce resource allocation.
The voltage and current of two adjacent substations are applied in calculating the ground fault.
Four types of AC system faults are applied in the PSCAD/EMTDC models of the CSG: a three-phase fault, a single-phase grounding fault, a two-phase grounding fault, and a two-phase short-circuit fault.
Three-phase short circuit faults are applied in the interregional liaison lines and the faults are cleared after a period of time.
The results demonstrate that CSF is an effective method for impulsive signature enhancement that could be applied in rotating machines for incipient fault detection.
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