scholarly journals Parametric Modeling and Moving Simulation of Vibrating Screen and Tubers on Potato Harvester

2015 ◽  
Vol 7 (6) ◽  
pp. 474-478
Author(s):  
Huali Yu ◽  
Xiaoshun Zhao ◽  
Yongying Sang ◽  
Tao Wu
2012 ◽  
Vol 195-196 ◽  
pp. 627-632
Author(s):  
Yong Ying Sang ◽  
Hua Li Yu ◽  
Jing Xia Jia

These In order to overcome the behindhand and inefficient design of potato diggers, feature-based parametric modeling software Autodesk Inventor was used for the modeling of potato diggers. The swing sieve, movement simulation with ADAMS was carried out. The complex velocity acceleration and displacement curves were analyzed. Collision pressure curves were analyzed too. νis less than or equal to 500 mm/s, and αis more than or equal to 2.5m/s2, and less than or equal to 20m/s2. Test results indicated that Collision pressures of small and medium tubers are 120 Newton and 250 Newton respectively, which are all smaller than damaging pressure. Potato can be transferred freely and damage rate is less than or equal to 4% when the frequency is 5.5Hz and the swing is 30mm. It satisfies the design request.


2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaodong Yang ◽  
Jida Wu ◽  
Haishen Jiang ◽  
Wenqiang Qiu ◽  
Chusheng Liu

Dynamic characteristic and reliability of the vibrating screen are important indicators of large vibrating screen. Considering the influence of coupling motion of each degree of freedom, the dynamic model with six degrees of freedom (6 DOFs) of the vibrating screen is established based on the Lagrange method, and modal parameters (natural frequencies and modes of vibration) of the rigid body are obtained. The finite element modal analysis and harmonic response analysis are carried out to analyze the elastic deformation of the structure. By using the parametric modeling method, beam position is defined as a variable, and an orthogonal experiment on design is performed. The BP neural network is used to model the relationship between beam position and maximal elastic deformation of the lateral plate. Further, the genetic algorithm is used to optimize the established neural network model, and the optimal design parameters are obtained.


Author(s):  
Na Tian ◽  
Huanyong Cui ◽  
Xiuhua Men ◽  
Ruichuan Li ◽  
Wenhui Yang ◽  
...  
Keyword(s):  

2004 ◽  
Vol 14 (06) ◽  
pp. 1975-1985
Author(s):  
RASTKO ŽIVANOVIĆ

The task of locating an arcing-fault on overhead line using sampled measurements obtained at a single line terminal could be classified as a practical nonlinear system identification problem. The practical reasons impose the requirement that the solution should be with maximum possible precision. Dynamic behavior of an arc in open air is influenced by the environmental conditions that are changing randomly, and therefore the useful practically application of parametric modeling is out of question. The requirement to identify only one parameter is yet another specific of this problem. The parameter we need is the one that linearly correlates the voltage samples with the current derivative samples (inductance). The correlation between the voltage samples and the current samples depends on the unpredictable arc dynamic behavior. Therefore this correlation is reconstructed using nonparametric regression. A partially linear model combines both, parametric and nonparametric parts in one model. The fit of this model is noniterative, and provides an efficient way to identify (pull out) a single linear correlation from the nonlinear time series.


1993 ◽  
Vol 10 (1) ◽  
pp. 5-8
Author(s):  
R. K. Mehta ◽  
R. R. Mallepali ◽  
C. W. Schultz

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