Non-random vibration analysis of rotate vector reducer

Zhang, Dequan; Li, Xing’ao; Yang, Meide; Wang, Fang; Han, Xu

doi:10.1016/j.jsv.2022.117380

Cited by 19 publications

(12 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where {𝜃 𝑚 ; 𝑚 = 1, … , 𝑛} is the unknown hyperparameter; and 𝑛 is the number of random variables. Assume that there are 𝑝 input sample points [𝐱 1 , … , 𝐱 𝑝 ] and the corresponding outputs are 𝐘=[𝑌 1 , … , 𝑌 𝑝 ], thus the scalars 𝛽 and 𝜎 2 𝑧 can be estimated as…”

Section: Kriging Modelmentioning

confidence: 99%

“…Structural reliability is focused on the ability of a structure to realize a specified function within a given time and condition. [1][2][3] The reason that the structure is required to ensure a certain level of reliability is that various uncertainties exist in the processing of structural design, manufacturing, usage, and maintenance, which brings serious and negative effects on structural safety, durability, and applicability. The stochastic reliability theory based on the probability limit state design method is a widespread approach to performing the structural reliability analysis.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Kriging‐based reliability analysis for a multi‐output structural system with multiple response Gaussian process

Qian

Wei

Huang

et al. 2023

Quality & Reliability Eng

View full text Add to dashboard Cite

This paper proposes an active learning Kriging (ALK) based reliability analysis method for a multi-output structural system by using a multiple response Gaussian process (MRGP) model. Firstly, various failure modes, including their interactions, are involved in a multi-output structural system. The MRGP model is used to construct the surrogate model directly because it can efficiently characterize the correlation between different failure modes. The particle swarm optimization (PSO) algorithm is integrated into the MRGP model to optimize the hyperparameter. Secondly, similar to ALK-based reliability method, three improved functions for these common learning functions (e.g., U-function, EFF-function, H-function) are proposed, which consider the distance requirement between the iteration sample point and training samples. Finally, the cross-validation methodology is employed as the stopping criterion and several numerical examples are provided to illustrate the effectiveness.

show abstract

Section: Kriging Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Kriging‐based reliability analysis for a multi‐output structural system with multiple response Gaussian process

Qian

Wei

Huang

et al. 2023

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…Therefore, analyzing the dynamic characteristics of RV reducers under nonlinear excitation holds significant theoretical research value for the stability control and dynamic performance optimization of RV reducer transmission systems. In recent years, research on the dynamic characteristics of RV reducers has predominantly focused on dynamic transmission errors [6][7][8][9][10][11][12][13][14][15], inherent properties [16][17][18][19], frequency-response characteristics [20,21], the dynamic performance of bearings within the system [22][23][24], and fault diagnosis based on dynamics [25]. Hidaka et al [6,7] established an equivalent mass-spring model for K-H-V-type reducers, laying the foundation for the dynamic analysis of RV reducers.…”

Section: Introductionmentioning

confidence: 99%

“…Wang et al [20] experimentally measured the torsional stiffness of the RV reducer, fitting the experimental results with trigonometric functions, and analyzed the amplitude-frequency characteristics and stability of RV reducers. Zhang et al [21] proposed a non-random vibration analysis method for RV reducers, aiming to assess the vibration of various components within RV reducers under uncertain excitations. Xu et al [22], considering the contact between the needle roller bearings and the inner and outer races, as well as the interaction between the needle roller bearing, the crankshaft, and the cam, presented a method for establishing a dynamic model of RV reducers based on contact multibody dynamics.…”

Section: Introductionmentioning

confidence: 99%

Study on Nonlinear Dynamic Characteristics of RV Reducer Transmission System

Han,

Wang,

et al. 2024

Energies

View full text Add to dashboard Cite

Rotate vector (RV) reducers have widely been used in high-performance precision drives for industrial robots. However, the current nonlinear dynamic studies on RV reducers are not extensive and require a deeper focus. To bridge this gap, a translational–torsional nonlinear dynamic model for an RV reducer transmission system is proposed. The gear backlash, time-varying mesh stiffness, and comprehensive meshing errors are taken into account in the model. The dimensionless vibration differential equations of the system were derived and solved numerically. By means of bifurcation diagrams, phase trajectories, Poincaré sections, and the power spectrum, the motion state of the system was studied with the bifurcation parameters’ variation, including excitation frequency and meshing damping. The results demonstrate that this system presents enriched nonlinear dynamic characteristics under different parameter combinations. The motion state of the system is more susceptible to change at lower frequencies. Increasing the meshing damping coefficient proves effective in suppressing the occurrence of chaos and reducing vibration amplitudes, significantly enhancing the stability of the transmission system.

show abstract

“…Chen et al [23] proposed a dynamic model for planetary gearboxes considering the clearance of the planet gear, sun gear and carrier bearings, as well as sun gear tooth crack levels. Zhang et al [24] proposed a non-random vibration analysis method for RV reducers based on the deterministic vibration model to analyze the vibration of its core components. Matejić et al [25] provided efficiency analysis for a new two-stage cycloid drive concept based on losses generated by friction, and drew comparisons with the current schemes in practice.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Modeling and Analysis of an RV Reducer Considering Tooth Profile Modifications and Errors

Huang

Ding

et al. 2023

Machines

View full text Add to dashboard Cite

Due to their advantages of compact size, high reduction ratio, large stiffness and high load capacity, RV reducers have been widely used in industrial robots. The dynamic characteristics of RV reducers in terms of vibratory response and dynamic transmission error have a significant influence on positioning accuracy and service life. However, the current dynamic studies on RV reducers are not extensive and require deeper study. To bridge this gap, a more effective and realistic lumped parameter dynamic model for RV reducers is developed, considering the tooth profile modification of cycloid gears and system errors. Firstly, for an efficient solution, the equivalent pressure angle and equivalent mesh stiffness of the cycloid–pin gear pair are introduced in the dynamic model based on the loaded tooth contact analysis. Secondly, the differential equations of the system are derived by analyzing the relative displacement relationships between each component, which are solved using the Runge–Kutta method. With this, the effects of errors such as machining errors, assembly errors and bearing clearances on the dynamic behaviors and transmission precision are investigated by comparison to quantify or qualify their influence. This research is helpful in characterizing the multi-tooth mesh and dynamic behavior, and revealing the underlying physics of the RV reducer.

show abstract

Non-random vibration analysis of rotate vector reducer

Cited by 19 publications

References 41 publications

Kriging‐based reliability analysis for a multi‐output structural system with multiple response Gaussian process

Kriging‐based reliability analysis for a multi‐output structural system with multiple response Gaussian process

Study on Nonlinear Dynamic Characteristics of RV Reducer Transmission System

Dynamic Modeling and Analysis of an RV Reducer Considering Tooth Profile Modifications and Errors

Contact Info

Product

Resources

About