An experimental study on high speed helical gears misalignments and dynamic behavior under random loading

Jammal, Ali; Gu, Chunguang; Wang, Hui; Li, Rongxue; Song, Yun Tao; Ye, Rong

doi:10.1109/icmae.2016.7549541

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…Zhang et al incorporated the unavoidable meshing errors in their study on the gear tooth modification (GTM) and provide an improved shape for the gear dynamic performance [16]. The effects of constant and fluctuating loads and the shaft speed on the helical gear dynamic response were used to establish a direct relation between shaft speed and its alignment [17]. With rising demand for electronic vehicles (EV), the dynamic requirements for the gear systems will change as it will be possible to run gears at higher speeds on electric motors compared to internal combustion (IC) engines.…”

Section: Introductionmentioning

confidence: 99%

Gear misalignment diagnosis using statistical features of vibration and airborne sound spectrums

et al. 2019

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Failure in gears, transmission shafts and drivetrains is very critical in machineries such as aircrafts and helicopters. Real time condition monitoring of these components, using predictive maintenance techniques is hence a proactive task. For effective power transmission and maximum service life, gears are required to remain in prefect alignment but this task is just beyond the bounds of possibility. These components are flexible, thus even if perfect alignment is achieved, random dynamic forces can cause shafts to bend causing gear misalignments. This paper investigates the change in energy levels and statistical parameters including Kurtosis and Skewness of gear mesh vibration and airborne sound signals when subjected to lateral and angular shaft misalignments. Novel regression models are proposed after validation that can be used to predict the degree and type of shaft misalignment, provided the relative change in signal RMS from an aligned condition to any misaligned condition is known.

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Section: Introductionmentioning

confidence: 99%

Gear misalignment diagnosis using statistical features of vibration and airborne sound spectrums

et al. 2019

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“…The tooth pro le has a crucial in uence on the wear performance of the gear. Helical gears has the characteristics of smooth meshing, high bearing capacity and low noise, therefore, helical gears were selected for the initial defect experiment [15][16][17]. The wear characteristics of gear with linear initial defects were studied through the self-built gear performance test bench.…”

Section: Introductionmentioning

confidence: 99%

Study on Wear Characteristics Evolution of Helical Gear With Linear Initial Defect

Zhu

Yuan

Guo

et al. 2021

Preprint

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The initial defects have greatly affected the gear transmission under harsh working conditions in the fields of wind power and ships. The influence of linear initial defects on the evolution of wear characteristics of helical gears was studied. The laser marking device was used to process the linear initial defect along the tooth width direction, and the gear without initial defect was used for comparison. It can be concluded that the linear initial defect changed the meshing state of the gear tooth, and greatly shortened the normal wear life of the gear, the normal wear life of the gear is shortened by about 45%, and the wear rate in the stable wear stage is increased by about 56%, a great deal of pitting corrosion and plastic flow on the tooth surface occurred in the pitch circle position of the defective gear. In addition, the lubrication condition deteriorated in the later period caused by lubricating oil pollution and the hard particles falling off the gearbox bearings entered the meshing surface and the emerged crack, which further accelerated the wear process of gear.

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“…A variety of models have been developed for the diagnostics of different faults, such as gear spalling or tooth breakage [7,[10][11][12], tooth crack [13][14][15][16], shaft misalignment [17,18], tooth surface pitting and wear [19][20][21][22][23][24][25]. More models have been developed to analyse the time varying mesh stiffness in a helical gear [26][27][28][29][30] and to study the effect of parametrical design on the dynamic behaviour of helical gear system [31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Helical gear wear monitoring: Modelling and experimental validation

Brethee

Zhen

et al. 2017

Mechanism and Machine Theory

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Gear tooth surface wear is a common failure mode. It occurs over relatively long periods of service nonetheless, it degrades operating efficiency and lead to other major failures such as excessive tooth removal and catastrophic breakage. To develop accurate wear detection and diagnosis approaches at the early phase of the wear, this paper examines the gear dynamic responses from both experimental and numerical studies with increasing extents of wear on tooth contact surfaces. An experimental test facility comprising of a back-to-back two-stage helical gearbox arrangement was used in a run-tofailure test, in which variable sinusoidal and step increment loads along with variable speeds were applied and gear wear was allowed to progress naturally. A comprehensive dynamic model was also developed to study the influence of surface wear on gear dynamic response, with the inclusion of time-varying stiffness and tooth friction based on elasto-hydrodynamic lubrication (EHL) principles.The model consists of an 18 degree of freedom (DOF) vibration system, which includes the effects of the supporting bearings, driving motor and loading system. It also couples the transverse and torsional motions resulting from time-varying friction forces, time varying mesh stiffness and the excitation of different wear severities. Vibration signatures due to tooth wear severity and frictional excitations were acquired for the parameter determination and the validation of the model with the experimental results. The experimental test and numerical model results show clearly correlated behaviour, over different gear sizes and geometries. The spectral peaks at the meshing frequency components along with their sidebands were used to examine the response patterns due to wear. The paper concludes that the mesh vibration amplitudes of the second and third harmonics as well as the sideband components increase considerably with the extent of wear and hence these can be used as effective features for fault detection and diagnosis.

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An experimental study on high speed helical gears misalignments and dynamic behavior under random loading

Cited by 4 publications

References 6 publications

Gear misalignment diagnosis using statistical features of vibration and airborne sound spectrums

Gear misalignment diagnosis using statistical features of vibration and airborne sound spectrums

Study on Wear Characteristics Evolution of Helical Gear With Linear Initial Defect

Helical gear wear monitoring: Modelling and experimental validation

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