Soft measurement model of ring's dimensions for vertical hot ring rolling process using neural networks optimized by genetic algorithm

Vertical hot ring rolling(VHRR) process has the characteristics of nonlinearity,time-variation and being susceptible to disturbance.Furthermore,the ring's growth is quite fast within a short time,and the rolled ring's position is asymmetrical.All of these cause that the ring's dimensions cannot be measured directly.Through analyzing the relationships among the dimensions of ring blanks,the positions of rolls and the ring's inner and outer diameter,the soft measurement model of ring's dimensions is established based on the radial basis function neural network(RBFNN).A mass of data samples are obtained from VHRR finite element(FE) simulations to train and test the soft measurement NN model,and the model's structure parameters are deduced and optimized by genetic algorithm(GA).Finally,the soft measurement system of ring's dimensions is established and validated by the VHRR experiments.The ring's dimensions were measured artificially and calculated by the soft measurement NN model.The results show that the calculation values of GA-RBFNN model are close to the artificial measurement data.In addition,the calculation accuracy of GA-RBFNN model is higher than that of RBFNN model.The research results suggest that the soft measurement NN model has high precision and flexibility.The research can provide practical methods and theoretical guidance for the accurate measurement of VHRR process.

A portable high precision three dimensional trace measuring system for underwater target with high speed

The paper describes a portable high precision three-dimensional trace measuring system for underwater target with high speed. The mathematical model for location, the main error sources, the calibration method for the underwater array and the way to correct its state are discussed. Problems about the distance ambiguity and multi-path interference are also analyzed. Part of experimental results on lake and at sea are given as well.

Marginal-restraint mandrel-free spinning process for thin-walled ellipsoidal heads

Metal sheet spinning is an advanced near-net forming technology for the manufacture of thin-walled ellipsoidal heads.The exact control of dimensional accuracy,however,is a considerable problem for spinning thinwalled parts with large diameter-to-thickness ratios.In this work,a marginal restraint mandrel-free spinning process with two passes is proposed for the fabrication of thinwalled ellipsoidal heads without wrinkling.A finite element model is established and verified to study the influences of spinning parameters on the dimensional precision of thin-walled ellipsoidal heads.It is found that the spinning parameters considerably influence the deviations of wall thickness and contour characteristics.A small forming angle or small roller fillet radius during the first pass spining,as well as the small angle between passes or high feed ratio during the second pass spinning,can improve the wall thickness precision.Meanwhile,as the forming angle or feed ratio is increased during the first pass spinning,the contour precision initially increases and then decreases.During the second pass spinning,the contour precision can be improved at a small angle between passes,whereas it deteriorates at a larger roller installation angle.The optimized spinning parameters are obtained and verified by experiments.