基于粒子群算法的提升机主轴装置应变测点优化研究

为更好地进行多绳摩擦提升机主轴装置应力应变研究,基于改进的粒子群寻优算法,对主轴装置的应变检测点实现了组合优化。首先,分析了主轴装置的力学模型,根据力学模型实现主轴装置有限元仿真及模态分析。根据仿真结果,初步选取特殊点作为主轴装置的应变测点;其次,以模态置信度准则为优化目标,基于粒子群算法对检测点实现组合优化,为防止优化过程中陷入局部最优,对粒子群做了交叉操作的改进;最后,以测点优化结果作为指导,在主轴装置相应位置粘贴应变片,利用无线应变仪实现各测点的应变检测。该研究方法为后续主轴装置故障诊断及摩擦提升机载荷检测的研究提供了数据基础。

Research on the Strain Measurement Point Optimization of Hoist Main Shaft Device Based on Particle Swarm Optimization

In order to better realize the stress and strain research of the main shaft of multi-rope friction hoist,the strain detection points of main shaft device were optimized based on the improved particle swarm optimization algorithm. Firstly, the mechanical model of the main shaft device was analyzed according to the finite element simulation and modal analysis. The special points were selected initially as the strain measuring point of the main shaft device based on the simulation results. Secondly, the modal assurance criterion was selected as fitness function, and combined optimization by particle swarm optimization (POS). In order to prevent the local optimization in the optimization process the cross-operation was introduced to improve the POS. Finally, according to the optimization result of the measuring points, the variable pieces were pasted on the corresponding position of the main shaft device. The strain detection of each measuring point was realized by using the wireless strain gauge. This method provides a data basis for the following research on the fault diagnosis of main shaft and the load detection of friction hoist.