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[期刊论文]

Resultant vibration signal model based fault diagnosis of a single stage planetary gear train with an incipient tooth crack on the sun gear

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author:

Liu, Xianzeng (Liu, Xianzeng.) [1] | Yang, Yuhu (Yang, Yuhu.) [2] | Zhang, Jun (Zhang, Jun.) [3] (Scholars:张俊)

Indexed by:

CPCI-S EI Scopus SCIE

Abstract:

Planetary gear trains equipped in wind turbine often run under slow speed and non-stationary load condition. The incipient gear faults in a wind turbine gearbox can hardly be detected yet might cause tremendous loss. In order to detect the incipient faults, a resultant vibration signal model is proposed to characterize the faulty features of a single stage planetary gear train working under non-stationary load conditions. For this purpose, an analytical dynamic model is developed. By introducing the crack-induced mesh stiffness and varying load into the dynamic model, the vibration responses of the system are predicted. Based on this, a resultant vibration signal model is developed in the form of weighted summation of mesh vibration signals. With the resultant model, the vibration signals of an example system are simulated and analyzed. The simulation results indicate that varying load and tooth crack make the system's vibration signals become extremely complicated in both time and frequency domains. The incipient tooth crack induced impulse vibration signals are too weak to be identified in the time domain but can be detected from the order spectrum. The simulation results from the resultant signal model are verified by the test rig experimental measurements. (C) 2018 Elsevier Ltd. All rights reserved.

Keyword:

Fault diagnosis Incipient tooth crack Planetary gear train Varying wind load Vibration analysis

Community:

  • [ 1 ] [Liu, Xianzeng]Tianjin Univ, Sch Mech Engn, Tianjin 300072, Peoples R China
  • [ 2 ] [Yang, Yuhu]Tianjin Univ, Sch Mech Engn, Tianjin 300072, Peoples R China
  • [ 3 ] [Zhang, Jun]Fuzhou Univ, Sch Mech Engn & Automat, Fuzhou 350116, Fujian, Peoples R China

Reprint 's Address:

  • 张俊

    [Zhang, Jun]Fuzhou Univ, Sch Mech Engn & Automat, Fuzhou 350116, Fujian, Peoples R China

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Related Article:

Source :

RENEWABLE ENERGY

ISSN: 0960-1481

Year: 2018

Volume: 122

Page: 65-79

5 . 4 3 9

JCR@2018

9 . 0 0 0

JCR@2023

ESI Discipline: ENGINEERING;

ESI HC Threshold:170

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 52

SCOPUS Cited Count: 63

30 Days PV: 0

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