文献类型：期刊文献

英文题名：A fuzzy logic neural network algorithm for compressor crankshaft-rolling bearing system optimization

作者：Zhang, Zheng[1];Zheng, Jianrong[1]

机构：[1]East China Univ Sci & Technol, Sch Mech & Power Engn, Shanghai 200237, Peoples R China

年份：2021

卷号：41

期号：4

起止页码：4891

外文期刊名：JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

收录：;EI(收录号：20214611158891);WOS:【SCI-EXPANDED(收录号:WOS:000716498300018)】；

语种：英文

外文关键词：Statically indeterminate problem; crankshaft-rolling bearing system; dynamics simulation; multi-objective optimization; implicit function

摘要：Taking the crankshaft-rolling bearing system in a certain type of compressor as the research objective, dynamic analysis software is used to conduct detailed dynamic analysis and optimal design under the rated power of the compressor. Using Hertz mathematical formula and the analysis method of the superstatic orientation problem, the relationship expression between the bearing force and deformation of the rolling bearing is solved, and the dynamic analysis model of the elastic crankshaft-rolling bearing system is constructed in the simulation software ADAMS. The weighted average amplitude of the center of the neck between the main bearings is used as the target, and the center line of the compressor cylinder is selected as the design variable. Finally, an example analysis shows that by introducing the fuzzy logic neural network algorithm into the compressor crankshaft-rolling bearing system design, the optimal solution between the design variables and the objective function can be obtained, which is of great significance to the subsequent compressor dynamic design.