Computational model for the analysis of bending fatigue in gears

Kramberger, Janez; Šraml, Matjaž; Glodež, Srečko; Flašker, Jože; Potrč, Iztok

doi:10.1016/j.compstruc.2003.10.028

Cited by 71 publications

(27 citation statements)

References 12 publications

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“…A tooth root crack typically starts at the point of the largest stress in the material. A computational model which applies the principles of linear elastic fracture mechanics could be used to simulate gear tooth root crack propagation (Kramberger, et al, 2004). Based on the computational results, the crack propagation path shows a slight curve extending from the tooth root as shown in Figure 6.…”

Section: Test Proceduresmentioning

confidence: 99%

“…The main idea of time series modeling is to fit the waveform data to a parametric time model and extract features based on this parametric model. The popular models used in the literature are the autoregressive (AR) model and the autoregressive moving average (ARMA) model (Kramberger, et al, 2004). In these models, only high order statistics of root mean square (RMS), crest factor and kurtosis are used.…”

Section: High Order Statisticsmentioning

confidence: 99%

See 1 more Smart Citation

Robust Prognostics Concept for Gearbox with Artificially Induced Gear Crack Utilizing Acoustic Emission

Abouel-Seoud¹,

Elmorsy²,

Dyab³

2011

EER

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Prognostic is a rapidly developing field and seeks to build on current diagnostic equipment capabilities for predicting the system state in advance. In machine condition prognostics, the current and past observations are used to predict the upcoming states of the machine. Signal-de-noising and extraction of the weak acoustic signature are crucial to gearbox prognostics since the inherent deficiency of the measuring mechanism often introduces a great amount of noise to the signal. In addition, the signature of a defective gearbox is spread across a wide frequency band and hence can easily become masked by noise and low frequency effects. As a result, robust concepts are needed to provide more evident information for gearbox performance assessment and prognostics. This paper introduces enhanced and robust prognostic concepts for gear tooth based on an optimal wavelet filter method for fault identification and a statistical method for performance degradation assessment. The experimental results demonstrate that the gear tooth defect can be detected and evaluated at an early stage of development when both the optimal wavelet filter and statistical analysis technique are used.

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Section: Test Proceduresmentioning

confidence: 99%

Section: High Order Statisticsmentioning

confidence: 99%

Robust Prognostics Concept for Gearbox with Artificially Induced Gear Crack Utilizing Acoustic Emission

Abouel-Seoud¹,

Elmorsy²,

Dyab³

2011

EER

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“…Many scholars at home and abroad are trying to seek a practical and convenient estimation model for crane in engineering application to analyze fatigue life [11]. Then structure analysis can be divided into the following processes as listed in Table 3.…”

Section: Struture Dynamic Analysismentioning

confidence: 99%

“…where K t is cable stiffness; n is is Cable wire rope segments; and E is referred to as a parameter along the direction of pull modulus five one amplitude cable wire rope, and design of the structure of wire rope cable joint department, here 0.8x10 11 Pa in the formula; A is section cable wire rope (mm 2 ); l is the cable length of steel wire rope (mm).…”

Section: The Finite Element Modeling Of Tower Body Structurementioning

confidence: 99%

The Fatigue Behavior Study of Intelligent Tower Crane by Finite Element Theory

Lu¹

2015

IJCA

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“…[e.g. Kramberger et al (2004)], it is generally treated as a (strain-controlled) short-cycle fatigue process. In other words, formation of fatigue cracks is assumed to be preceded by the operation of highlylocalized plastic-deformation processes.…”

Section: Fatigue-crack Initiationmentioning

confidence: 99%

Finite-element Analysis of Horizontal-axis Wind-turbine Gearbox Failure via Tooth-bending Fatigue

Grujičić¹,

Galgalikar²,

Ramaswami³

et al. 2014

International Journal of Material and Mechanical Engineering

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Wind energy is one of the most promising and the fastest growing alternative-energy production technologies which have been developed in response to stricter environmental regulations, the depletion of fossil-fuel reserves, and the world's ever-growing energy needs. This form of alternative energy is projected to provide 20% of the US energy needs by 2030. For economic reasons, wind turbines (articulated structures which convert wind energy into electrical energy) are expected to operate, with only regular maintenance, for at least twenty years. However, some key wind-turbine components (especially the gearbox) tend to wear down, malfunction and fail in a significantly shorter time, often three to five years after installation, causing an increase in the wind-energy cost and in the cost of ownership of the wind turbine. Clearly, to overcome this problem, a significant increase in long-term gearbox reliability needs to be achieved. While purely empirical efforts aimed at identifying shortcomings in the current design of the gearboxes are of critical importance, the use of advanced computational methods engineering analyses can also be highly beneficial. The present work demonstrates the use of the finite element analysis in modeling and elucidating the root cause of one of the gear failure modes (i.e. toothbending fatigue) under a variety of normal operating and extreme wind-loading conditions.

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Computational model for the analysis of bending fatigue in gears

Cited by 71 publications

References 12 publications

Robust Prognostics Concept for Gearbox with Artificially Induced Gear Crack Utilizing Acoustic Emission

Robust Prognostics Concept for Gearbox with Artificially Induced Gear Crack Utilizing Acoustic Emission

The Fatigue Behavior Study of Intelligent Tower Crane by Finite Element Theory

Finite-element Analysis of Horizontal-axis Wind-turbine Gearbox Failure via Tooth-bending Fatigue

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