Finite Element Analysis For Bucket Wheel Stacker-reclaimer And Optimal Design For The Structure Of Forearm

In this paper, the bucket wheel stacker-reclaimer, DQLK1500/2500.35, wasselected as the research object. Calculate the loads suffered by the machine underdifferent conditions. Select the three most typical operating conditions, that is, by themain load, work and non-work conditions to carry out finite element analysis of themetal structure of the machine. The analysis results showed that: the overallstructural strength, stiffness and stability all meet the design requirements, but theforearm frame structure strength storage is too large, which is not only a waste ofmaterials, but also has a bad effect on the stability of the whole machine.The bucket wheel stacker-reclaimer design process optimization forearm framestructure is as follows: first, using the of language ANSYS APDL to buildparameterized finite element model; second, according to modern structuraloptimization theory and methods, building a section of the main dimensions of thestructure optimize the design variables, the total mass of the structure of theobjective function, all the conditions for the structure of maximum stress statevariables, the design requirements for optimizing the design model constraints; third,given the structure optimization model for multi-variable, the feasible region is notcontinuous, the characteristics of large amount of calculation, use genetic algorithmto solve the optimization problem: learning from past results and test value methodis set to run the process of genetic operators, including evolutionary process calculuspopulation size, selection rate, crossover rate, mutation rate, and convergenceconditions evolution algebra; forth, the finite element analysis software ANSYS andMATLAB software combines numerical calculation using VB language will be bothintegrated truss structure to obtain the optimal solution of forearm.When using genetic algorithm optimization design problem, the value of geneticoperators greater flexibility, there will be a certain degree of influence on the resultsobtained optimal solution. For further investigate the genetic operators to optimizethe sensitivity of the results in this paper optimization problem solving process,specially select different genetic operators to obtain the corresponding optimal value. The results showed that: first, when using genetic algorithm to solve optimizationdesign problem, the value of genetic operators is different, the optimization resultswill be influenced; second, when the value is not the same genetic operators tooptimize the objective function of the total design problem is to maintain adownward trend, the corresponding values are always not only increased fitness,outstanding individuals will be retained, poor adaptability individuals soon beeliminated, in line with the natural world "eugenics and eliminating the inferior"rules of survival; third, in the genetic algorithm iterative process of evolution, as astate variable structure is not monotonic approaching maximum stress allowablestress values, but there are some ups and downs, this mutation and geneticalgorithms randomness, uncertainty highly consistent.Combined with genetic algorithm to obtain the optimal solution theory, furtheraccording to the requirements implicit actual machining, has been both to meet thestrength, stiffness, stability and meet the functional requirements of the structure.Not only saves material, but also created a certain economic benefits, explored arapid design method available for bucket wheel stacker-reclaimer designersreference, for rapid design of mechanical structures, lean design has a certainsignificance.