Study on Prediction of Rod Mechanical Damage Based on Particle Population Convolution Algorithm
There are mechanical damage phenomena in the actual use of universal rotating machinery rotating rod.The traditional prediction methods rely on empirical formulas and simple statistical models,and it is difficult to accurately capture the complex stress state and damage evolution process of the rota-ting rod in the actual working environment.Therefore,these methods have limitations in the prediction ac-curacy,and it is difficult to achieve early damage warning and life prediction.Combined with convolutional neural network and particle swarm optimization algorithm,a kind of mechanical damage prediction of rota-ting rod based on particle swarm optimization algorithm was proposed.By comparing with actual mechani-cal damage,mechanical damage prediction can be realized to avoid the network falling into local optimal,and the calculation efficiency and prediction accuracy are improved,meeting the needs of mechanical dam-age prediction of rod in practical engineering.
particle group convolution algorithmrotation barmechanical damageprediction
万方数据
维普
