Research On The Dropping Shock Response Of Pruning Machine Based On LS-DYNA And BP Neural Network

Due to the influence of the sharply collision,many mechanical and electrical products resulting in the failure of the service life.Drop impact is the main failure form of garden pruning machine.At present,the electric garden pruning tool products design with the original design,prototyping,drop test,the traditional mode of product optimization design.The design and development mode of traditional product spends a lot of manpower and cost,it has become increasingly unsuitable for small electromechanical products,especially the market demand of personalized electric garden pruning products that have complex structures.Therefore,it has become a hot issue to be solved for researching economical,practical and accurate design and development mode of pruning machine,establishing a new method for predicting the impact performance of pruning machine,and designing reasonable cushioning composite material structures.Supported by “R & D and industrial applications of high efficiency long life and low noise blade cutting system” which is one of major projects of industrial technology innovation in Ningbo(2015B11031),this paper researches drop impact response of a certain type of garden pruning machine.It makes a deep research on several aspects including with the drop simulation and test of drop garden pruning machine,structure optimization design,the establishment of BP neural network prediction model and the design of cushioning protection composite structures.Aiming at the uncertainties during the dynamic drop process of garden pruning machine with complex internal structures,we make the finite element simulation analysis to analyze the drop processes of the pruning machine by using Hypermesh and ANSYS/LS-DYNAcosimulation technology in this paper.There are two extreme working conditions,lateral drop and vertical drop in the processes.Then,on-site drop test of the pruning machine is carried out under the same conditions.Comparing and analyzing the results of contrast drop simulation and drop test,we can find the vulnerable parts which affect the service life of the pruning machine after dropping.Then,after the fall of the garden pruning machine,the structural optimization design of the vulnerable components is carried out in the Hypermesh,after which that the finite element simulation analysis of the fall of the new pruning machine model in the horizontal drop and the vertical lateral drop was carried out to verify whether the improved machine model met the requirements.A total of 20 sets of maximum impact stress samples obtained via the main components(i.e.,gearbox and rotary tube)of the pruning machine dropping at different drop conditions by the original pruning machine fall simulation parametric model which was fit to the actual situation of pruning machine falling were used for training and verification of neural networks.The finite element simulation technique and the neural network were used to predict the maximum stress value of the main components of the garden pruning machine under different falling shock conditions and provide a new reference for the reliability test and reliability evaluation of the garden pruning machine by establishing the BP neural network model between the drop height,the drop angle,the ground material and the maximum impact stress value of the main components.Reduced the drop simulation time.Finally,the buffer protection composite structures with the better performance were designed by combining with the impact test and finite element simulation,which can be widely used in the transport packaging products to avoid damages caused by dropping in the transport,stacking and other processes.