2020
DOI: 10.1177/0957456520948273
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A new fault feature extraction method of rotating machinery based on finite sample function

Abstract: Feature extraction plays a crucial role in the diagnosis of rotating machinery’s faults. In order to separate different fault vibration signals from measured mixtures and diagnose the fault features of the machine effectively according to the separated signals, a blind source separation (BSS) method using kernel function based on finite support samples was proposed. The method is stronger adaptability to the score functions estimated according to finite support observed signal samples. The simulation results p… Show more

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Cited by 1 publication
(2 citation statements)
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“…where fitness denotes the goal function, γ ¼ fK, αg are the VMD parameters for joint optimization, WCK k ðk ¼ 1, 2, /, KÞ denotes the WCK of the k -th mode. In this research, K is an integer valuing in interval [2,10], α takes a real number in interval [1000, 10, 000]. The flow chart of the developed VMD method is displayed in Figure 1.…”
Section: Developed Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…where fitness denotes the goal function, γ ¼ fK, αg are the VMD parameters for joint optimization, WCK k ðk ¼ 1, 2, /, KÞ denotes the WCK of the k -th mode. In this research, K is an integer valuing in interval [2,10], α takes a real number in interval [1000, 10, 000]. The flow chart of the developed VMD method is displayed in Figure 1.…”
Section: Developed Methodsmentioning
confidence: 99%
“…Therefore, the fault diagnosis of rolling bearings and gears in rotating machinery has attracted a lot of attention recently. [1][2][3][4] Vibration signal analysis is the most widely adopted method for rotating machinery fault diagnosis. In engineering, mechanical vibration response is the superimposition of multifrequency characteristic information.…”
Section: Introductionmentioning
confidence: 99%