A Method for Analysing Gearbox Faults Using Time–frequency Representations

Oehlmann, Harald; Brie, David; Tomczak, Marc; Richard, Alain

doi:10.1006/mssp.1996.0093

Cited by 48 publications

(25 citation statements)

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“…For the FE analysis of the gearbox, existing literatures [23][24][25][26][27][28] generally only consider the influence of lubrication oil concerning lubrication and cooling. Actually, lubrication oil itself will affect the natural modal, dynamic response, and other dynamic characteristics of the whole gearbox system.…”

Section: Fluid-solid Coupling Gearbox Modelmentioning

confidence: 99%

New Method with Experimental Validation for Power Transmission Process Analysis on Herringbone Gear Train System

Wang¹,

Xing²,

Fang³

2017

IJAV

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To analyse the power transmission process of herringbone gear train system supported by rolling element bearings more accurately, meshing stiffness calculation method is firstly developed through tooth load contact analysis. The model of mesh impact force and the approach to calculate the equivalent friction torque coefficient in mixed elastohydrodynamic lubrication state are sequentially derived. The twelve-degree-of-freedom herringbone gear vibration model is finally established. Upon the consideration of different supporting ways between pinion and gear shaft, dynamic loads on support bearings are calculated separately. Based on rolling element bearing dynamic model and internal load distribution on bearings, comprehensive analysis of the vibration transmission process in meshing gear pair, rolling element bearings, and internal walls of gearbox bearing holes is conducted. Under the real dynamic load boundary condition, harmonic response and transient response of gearbox are obtained correspondingly. To evaluate the proposed model approach, a rolling element bearings support herringbone gear system is adopted to do real closed power flow vibration test. Simulation and experimental results show that the theoretical analysis in this paper is scientific and reasonable to calculate the dynamic load transfer process, and the maximum relative deviation between the theoretical results and the experimental data is less than 15%.

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Section: Fluid-solid Coupling Gearbox Modelmentioning

confidence: 99%

New Method with Experimental Validation for Power Transmission Process Analysis on Herringbone Gear Train System

Wang¹,

Xing²,

Fang³

2017

IJAV

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show abstract

“…The target of paper in hand is the detection and diagnosis of faults and damages at gear drives under special operational conditions and limited hardware conditions. In contrast to the already known and applied approaches [8][9][10][11], we must reach this target by measurement under strong unsteady operational conditions, e.g. during a fast start up or run down.…”

Section: Tqa Of Time-equidistant Sampled Measuring Datasmentioning

confidence: 99%

Fault Detection in Gear Drives With Non-Stationary Rotational Speed - Part Ii: The Time-Quefrency Approach

Meltzer¹,

IVANOV²

2003

Mechanical Systems and Signal Processing

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“…It has three planet sets (1), (2) and (3) with the transmission ratios i 1 ¼ 1:6329; i 2 ¼ 0:6207 and i 3 ¼ 3:0588 resp. in a housing (4). Each of the planet set consists of one central gear wheel, one annulus wheel (ring wheel) and three planet wheels with a common planet carrier.…”

Section: Tfa On the Basis Of Distributions Of Cohen Classmentioning

confidence: 99%

“…All papers, which we have found until now, described the detection of faults via the analysis of short transient vibration midst of a stationary acceleration signal, which was generated by the tooth meshing with steady rotational speed [4][5][6]9]. In contrast to this approach, we tried to solve the task of fault diagnosis of gears at strong unsteady rotational speed, which was caused by the special unsteady controlled test runs in the factory.…”

Section: Introductionmentioning

confidence: 99%

“…The result of this analysis is a set of temporary spectra along the time axis, the so-called time-frequency distribution TFD X ðt; oÞ: Quadratic forms of TFD lead to the joint temporary distribution of signal energy along the time-axis and the frequency-axis. On the field of gear diagnostics mostly the TFA of Cohen class [4][5][6] as well as wavelets [7,8] are applied. We confine ourself in this paper to the application of Cohen class.…”

Section: Introductionmentioning

confidence: 99%

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Fault Detection in Gear Drives With Non-Stationary Rotational Speed-Part I: The Time-Frequency Approach

Meltzer

Ivanov

2003

Mechanical Systems and Signal Processing

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A Method for Analysing Gearbox Faults Using Time–frequency Representations

Cited by 48 publications

References 0 publications

New Method with Experimental Validation for Power Transmission Process Analysis on Herringbone Gear Train System

New Method with Experimental Validation for Power Transmission Process Analysis on Herringbone Gear Train System

Fault Detection in Gear Drives With Non-Stationary Rotational Speed - Part Ii: The Time-Quefrency Approach

Fault Detection in Gear Drives With Non-Stationary Rotational Speed-Part I: The Time-Frequency Approach

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