Obtaining and Predicting of Equivalent Load Spectrum for Overhead Traveling Crane Based on Support Vector Machines

Abstract

Crane load spectrum is the basis data of the evaluation of fatigue life, obtaining the large samples data need to consume large amount of time and finance. For exploring and initiating a new way of obtaining and predicting the crane load spectrum, the present essay uses Support Vector Machines (SVM) to establish the non-linear mapping relation between this type of crane's work cycles and different rated weights and lifting loads, namely equivalent load spectrum of crane. The Engineering example demonstrates: it is feasible to construct the equivalent load spectrum for some type of crane using SVM. Meanwhile, the equivalent load spectrums of the typical or future crane in this type could be obtained and predicted through the trained SVM model. It has provided the reliable data for the reliability analysis and fatigue life prediction of crane.