首页|Studies from Nanjing University of Science and Technology Describe New Findings in Support Vector Machines (Detecting Preload Degradation of a Ball Screw Feed S ystem Using High-frequency Reconstruction and Support Vector Machine)
Studies from Nanjing University of Science and Technology Describe New Findings in Support Vector Machines (Detecting Preload Degradation of a Ball Screw Feed S ystem Using High-frequency Reconstruction and Support Vector Machine)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Support Vector Ma chines are discussed in a new report. According to news reporting originating fr om Nanjing, People's Republic of China, by NewsRx correspondents, research state d, "Ball screws need to be applied with different preloads in most applications, however, very few studies had paid attention to preload detection, which is one of the most common failure modes of ball screws. To detect the preload of a bal l screw, we propose a novel approach using vibration signals and ensemble empiri cal mode decomposition (EEMD) combined with linear discriminant analysis (LDA) a nd a support vector machine (SVM)." Funders for this research include National Natural Science Foundation of China ( NSFC), National Science and Technology Major Projects of China, Open Fund of Key Laboratory of CNC Equipment Reliability of Jilin University.
NanjingPeople's Republic of ChinaAsiaEmerging TechnologiesLinear Discriminant AnalysisMachine LearningSuppor t Vector MachinesVector MachinesNanjing University of Science and Technology
NETL
NSTL
