Optimization Method Study Of Bridge Crane Girder Based On Improvement Of Glowworm Swarm Optimization

Bridge crane is an indispensable lifting equipment in the manufacturing industry,which can improve the transportation efficiency and reduce the labor intensity.In order to overcome the shortcomings of the traditional optimization design method about bridge crane including,poor effect of weight loss,low operational efficiency and complex problem can not be calculated.we try to optimize the size of the bridge crane main girder by the Glowworm Swarm Optimization(GSO).The GSO method could not only satisfy to production requirement,but also make the quality lighter than other methods.The main contents of this paper are as follows:(1)The paper analyze the research status of GSO and crane at home and abroad,and the algorithm disadvantages such as slow convergence rate and easy to fall into the local optimal solution.Then,puts forward the optimization of the bridge crane main girder based on Improvement of Glowworm Swarm Optimization(IGSO).(2)The paper study the key steps in the optimization process of GSO,introduce the foraging behavior strategy and adaptive inertia weight into the basic GSO,reintegration the improved algorithm and simulated annealing algorithm,and finally form the IGSO.The improved algorithm is tested by two typical functions and compared with the optimized data before optimization,the results show that IGSO has rationality and feasibility on the algorithm performance and optimization results.(3)Through analyze the model to determine the optimization process,and further study the main beam structure and load distribution characteristics.Finally,by selecting the design variables,establish the objective function and constraints,including strength,stiffness,stability and border size etc.Based on these conditions,establish the corresponding mathematical model of the optimal design about cross-sectional area size.(4)The box girder of a certain type of bridge crane is taken as the research object,and the main parameters in the algorithm are tested several times to determine the optimal parameters which are most suitable for IGSO.The optimal cross-sectional area of ??the main beam is optimized with the optimal set of control parameters.The optimization results show that compared with the initial main beam,cross-sectional area of IGSO algorithm decreased 20.86%.Finally,the optimization comparison of models before and after verified that the strength and stiffness after optimal are meet to the actual engineering requirements through ANSYS Workbench.