Optimazition-Design And Research Of Crane’s Trolley Structure

Energy-saving has become an important issue in the world for sustainable development. Engineering equipment’s self-weight is very high. So, it is very important to carry out energy-saving design to promote the development of a low-carbon economy. Lightweight has becoming the trend of lifting equipment’s development.Crane’s trolley structure is a statically indeterminate structure welded by steel, traditional calculation method is simplified it to a few beams to design, and this method ignores its eccen-tric load effect. Trolley designed by traditional method improves its stiffness by increasing trolley’s height. In order to ensure mechanism working normally fixed on it. Generally, we lower allowable stress to ensure stiffness. So,this design is a waste of material and this method is conservative.This thesis takes the32t-L single-girder crane’s trolley as account, based on FEM and structural optimization. To model its finite model on ANSYS by element shel163, after solving, structural displacement and stress are obtained, then, the trolley’s optimization is carriedo on by Multi-optimization by software ISIGHT.The finite element model is established by shel163and mass21element in ANSYS.Static and modal are solved to obtain its displacement and stress and check its stiffness and intensity.The optimal Latin hyper-cube is used to select the enormous influence design variables through DOE and sensitivity methods. The optimization problem space is decreased and the efficiency is increased.Response surface method is used to establish the quadratic RSM approximation model. In order to increase optimal efficiency, the approximation is used to carry on optimization-Overall optimization method has better optimal ability in all.But; numerical optimization method has a fast speed. The MIGA and Hooke-Jeeves are used to establish the combination optimization method to solve the trolley’s structural chararistic.Which optimazition method is used to solve the problem, According to the problem’s complexity and the quantity of variables.