Finite element explicit dynamics simulation of motion and shedding of jujube fruits under forced vibration

Zhou, Jie; Li, Xu; Zhang, Aiqi; Hang, Xiaochen

doi:10.1016/j.compag.2022.107009

Cited by 18 publications

(10 citation statements)

References 22 publications

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“…ω i is the ith order modal frequency, and the modal oscillation of the response is φ i . For φ i , where i ranges from 1 to N, we can transform the physical coordinates into modal coordinates [16][17][18][19].…”

Section: Modal Analysis Theorymentioning

confidence: 99%

The dynamic investigation of intrinsic vibration characteristics of a stranding machine by the finite element method

et al. 2023

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In response to the design problems of violent vibration and noise when a stranding machine is running at high speed, this project completed a motion simulation and vibration analysis based on the prototype FB-650C-2 bow-type stranding machine produced by Fuchuan Mechanical and Electrical Technology Co. The modal analysis was carried out in ANSYS to obtain the first eight orders of inherent frequencies and vibration patterns, combined with excitation force analysis to verify whether the rotating parts could avoid the resonant frequency when operating. Harmonic response analysis was carried out based on the modal state to calculate the steady-state forced vibration of the structure, and the variation curve of response value (usual deformation) with frequency and the cloud diagrams of stress distribution of each component at the rotation frequency were obtained. Suggestions for improving vibration and reducing noise were made based on the experimental and analytical results.

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Section: Modal Analysis Theorymentioning

confidence: 99%

The dynamic investigation of intrinsic vibration characteristics of a stranding machine by the finite element method

et al. 2023

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“…In the response of a nonlinear system, the primary resonances are the excitation frequency, close to the natural frequency, and the sub-harmonic resonance, close to an integer multiple of the natural frequency [31]. The frequency domain signal of the soil is very complex after being vibrated.…”

Section: Frequency Domain Responsementioning

confidence: 99%

Vibration Response of Soil under Low-Frequency Vibration Using the Discrete Element Method

Wan,

Li,

Song

et al. 2023

Agriculture

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The vibration response of soil is a key property in the field of agricultural soil tillage. Vibration components of tillage machinery are generally used to reduce tillage resistance and improve work efficiency, and the pressure variation under low-frequency vibration will affect the fragmentation and dispersion of farmland soil. However, the gradient of pressure variation, frequency domain response, and effective transmission range is unclear. A new method based on the DEM (discrete element method) is presented to study the vibration response and pressure transmission under low-frequency vibration. Bench test results have shown that peak pressure positively correlates with the vibration frequency and attenuates rapidly at a vibration distance of 100 to 250 mm. The resulting data were also selected to determine the simulation model’s parameters. Amplitude, vibration frequency, and soil depth were used as test factors in single-factor simulation tests, and their effects on the peak pressure, frequency domain response, and effective transmission distance were analyzed. The results showed a positive relationship between the peak pressure and the test factors. The peak pressure increased with a maximum gradient of 19.02 kPa/mm at a vibration distance of 50 mm. The amplitude, vibration frequency, and soil depth positively correlated with the dominant frequency amplitude. The main frequency was independent of amplitude and soil depth. At a vibration distance of 250 mm, the dominant frequency was approximately twice the vibration frequency at 7–11 Hz and approximately equal to the vibration frequency at 13–15 Hz. Multiple exponential functions were used to fit the peak pressure attenuation function, obtaining an effective transmission distance range of 347.15 to 550.37 mm for the 5 kPa cut-off pressure. For a soil depth of 300 mm, the vertical shear wave diffusion angle was greater than the horizontal shear wave diffusion angle. This study clarifies the vibration response of soil under low-frequency vibration, which helps to design vibration-type, soil-engaging components of tillage machinery and match vibration parameters for energy-saving and resistance reduction purposes in soil tillage.

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“…In order to avoid subjective factors in order determination of subspace algorithms, automatically identifying accurate order can improve the reliability of the modal identification algorithm (Reynders et al, 2012; Häckell and Rolfes, 2013; Zhou et al, 2022a). Commonly used time domain automatic identification methods include hierarchical clustering algorithms (Ubertini et al, 2013) and non-hierarchical clustering algorithms (Verboven et al, 2002; Vanlanduit et al, 2003) in the intelligent algorithm.…”

Section: Introductionmentioning

confidence: 99%

Automatic modal identification based on similarity filtering and fuzzy clustering

Jiang

Wang

et al. 2023

Journal of Vibration and Control

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Artificially determining the model order is necessary for time domain modal identification, which affects the identification efficiency and accuracy. An automatic identification method is proposed to determine the best estimation of the model order. Based on the covariance-driven stochastic subspace identification method (SSI-COV), the singular value decomposition of the Toeplitz matrix is carried out to determine the range of the lower triangular matrix. The similarity coefficient and distance function are introduced to cluster the modes, and the poles of the false modes are removed to obtain the clustering stabilization diagram. The model order is taken as the number of clustering centers of the fuzzy c-means (FCM) algorithm, and all the poles of the stabilization diagram are clustered to get the modal parameters of each order. The effectiveness of the proposed method is verified by adopting a thin-walled cylindrical column, a triangular-prism truss in simulation, and a flexible beam in experiment. The robustness of the method is illustrated by adding white noise to the simulated response data. The advantage of the clustering stabilization diagram is demonstrated by comparing with the traditional stabilization diagram.

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Finite element explicit dynamics simulation of motion and shedding of jujube fruits under forced vibration

Cited by 18 publications

References 22 publications

The dynamic investigation of intrinsic vibration characteristics of a stranding machine by the finite element method

The dynamic investigation of intrinsic vibration characteristics of a stranding machine by the finite element method

Vibration Response of Soil under Low-Frequency Vibration Using the Discrete Element Method

Automatic modal identification based on similarity filtering and fuzzy clustering

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