Soft-Sensing Model of Deformation of Welded Steel Structure Based on FLS-SVM and its Application
To effectively achieve rapid and high-precision measurements of the deformation of steel welded structure, multiple sets of the actual experimental data of steel welded structure are used as the samples, the soft-sensing model of deformation of welded steel structure, which uses the welding current I, the welding voltage U, the welding speed v and the flow of gas qm as arguments, is established by fuzzy least squares support vector machine, and adaptive genetic algorithm is used to optimize the number of positive gasification rules c and the parameters of kernel function σ, training, testing and practical application results show, the optimization of 200 steps, the training relative error which become saturated is 2.43%, the testing relative error is less than 2.45%.
J. P. Lei and J. M. Chen, "Soft-Sensing Model of Deformation of Welded Steel Structure Based on FLS-SVM and its Application", Applied Mechanics and Materials, Vol. 628, pp. 152-156, 2014