Numerical and experimental study of gear rattle based on a refined dynamic model

Dong, Guobo; Yi, Zhou; Wang, Yawen; Chen, Fangchao; Shi, Xiaohui

doi:10.1016/j.apacoust.2021.108407

Cited by 16 publications

(7 citation statements)

References 27 publications

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“…The results are consistent with the assumptions made in many researches, such as in Ref. [24,37], and to some extent, verify the correctness of the proposed lubrication model. As the load decreases to 100Nm and 50Nm, the difference in the RMS values of DTE at each rotational speed calculated by the two models increases.…”

Section: Effect Of Lubricationsupporting

confidence: 90%

Load-dependent dynamic model of spur gear considering effects of oil film

Cao

Rao

Chen

2023

Preprint

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Gear system is usually lubricated to generate an oil film to avoid dry contact at the mesh interface. As the oil film separates the engaging gear teeth, its effect on the transmission error (TE) is opposite to the teeth elasticity. How to consider the combined influence of the oil film and the tooth elasticity on the TE, and further on the dynamic performance of gears, is still not revealed completely. In this paper, a new mesh stiffness (MS) involving the effect from the oil film and the tooth elasticity is defined, and a nonlinear dynamic model of a spur gear system with developed MS and drive-side and back-side contact is proposed. The effect of the oil film on the dynamic responses of the gear pair is revealed by comparing the received results with that from the dry contact situation and the experiment. It is indicated that the oil film will affect the effective MS and dynamic transmission error (DTE) of the gear system, especially under the situation with the light load. For a tip relived gear pair, the dynamic load sharing ratio (DLSR) between teeth pairs changes significantly when the lubrication is considered.

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Section: Effect Of Lubricationsupporting

confidence: 90%

Load-dependent dynamic model of spur gear considering effects of oil film

Cao

Rao

Chen

2023

Preprint

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“…5 and Table 1, and the difference between different churning torque calculation models under the same conditions is more obvious, indicating that there is still a lack of a more unified and effective churning torque theoretical calculation model. Guo et al [27,28] established a theoretical calculation model of gear churning resistance torque from the mechanism of gear dragging torque, using the theory of fluid attachment layer and fluid momentum theorem, taking into account the multi-parameter influence characteristics of gear transmission system, the dynamic change characteristics of gear end velocity, the dynamic change law of fluid attachment layer and the change rate of lubricant volume in the meshing area, and verified the feasibility of the model through tests.…”

Section: Drag Torquementioning

confidence: 99%

Nonlinear characteristic analysis of gear rattle based on refined dynamic model

Dong

Ning

et al. 2022

Nonlinear Dyn

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In order to explore the vibration response and the nonlinear behavior of gear rattle, a nonlinear dynamic model is developed in this paper considering the nonlinear oil film force, timevarying meshing stiffness, dragging torque and friction and gear backlash with time-varying characteristics. The time-varying meshing stiffness is calculated using the potential energy method. Considering the convolution and extrusion of the lubricant between the teeth, it is modeled as a nonlinear spring-damped element and a nonlinear oil film force is introduced. The drag torque is calculated numerically using fluid dynamics theory, friction principle, momentum conservation principle and Bernoulli's principle. The model is verified by comparing the bench test results with the simulation results, and the parametric study is performed to investigate the nonlinear system characteristics by means of Fast Fourier Transform, Poincare map and bifurcation diagram. The results show that as the excitation frequency increases, the system enters chaotic state under multiple frequency jumps. Excessive torque fluctuation may lead to severe rattling phenomenon of the gear pair, and making the system enter a chaotic state; As the lubricant viscosity increases, the system shows periodic, bifurcation and chaotic behavior alternately, and when the viscosity is large enough, the high frequency shock intensity decays more rapidly due to large drag torque, which is beneficial to reduce the percussion strength and prevent the system into chaos.

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“…This method divides the 3D scene into multiple focal lengths according to the distance, transmits signals to different focal length to achieve the purpose of real-time imaging, which can improve the problems of slow calculation speed and low sparsity rate of beamforming technology on sparse array. To make up for the shortcomings of microphone signal pickup performance and signal post-processing technology, Guo [35] first uses beamforming algorithm to suppress noise, then uses the optimal improved logarithmic spectral amplitude combined with depth neural network to train the masking value of multi-objective function, and proposes a filtering method to eliminate residual noise signal; the algorithm is robust to speech signal input in non-ideal state. The adaptive beamforming algorithm has made great contribution to improve the robustness and pick-up quality of speech identification technology.…”

Section: Beamforming Algorithmmentioning

confidence: 99%

A review for the noise source identification methods based microphone array

Hou¹,

Zeng²,

Deng-feng³

et al. 2022

J. vibroeng.

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Sound source identification is an important prerequisite for noise control. In recent years, new methods of sound source identification have been developed to improve the robustness of source identification. In this paper, a comprehensive review of noise source identification methods is developed to summarize its developing status and engineering applications. At first, a microphone array which is to acquire the sound pressure field is described. And then, the sound field visualization methods (beamforming and acoustic holography) and their advantages and disadvantages are reviewed. Finally, to improve the identification accuracy of the moving sound source, the hybrid acoustic holography methods with more generality and robustness are reviewed. Through the comparison and summary of the sound source identification methods, we expect this work may provide a potential guidance for the subsequent research studies in the field of sound source identification.

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Numerical and experimental study of gear rattle based on a refined dynamic model

Cited by 16 publications

References 27 publications

Load-dependent dynamic model of spur gear considering effects of oil film

Load-dependent dynamic model of spur gear considering effects of oil film

Nonlinear characteristic analysis of gear rattle based on refined dynamic model

A review for the noise source identification methods based microphone array

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