机译:基于改进的超球结构多类支持向量机的滚动轴承故障位置分类和性能退化程度
School of Electronics and Information Engineering, Harbin Institute of Technology, No. 92, West Dazhi Street, Harbin 150001, PR China, School of Electrical and Electronic Engineering, Harbin University of Science and Technology, No. 52, Xuefu Rd, Harbin 150080, PR China;
School of Electrical and Electronic Engineering, Harbin University of Science and Technology, No. 52, Xuefu Rd, Harbin 150080, PR China, Radiophysics and Electronics Department, Belarusian State University, Minsk 220030, Belarus;
School of Electronics and Information Engineering, Harbin Institute of Technology, No. 92, West Dazhi Street, Harbin 150001, PR China;
School of Electrical and Electronic Engineering, Harbin University of Science and Technology, No. 52, Xuefu Rd, Harbin 150080, PR China;
School of Electrical and Electronic Engineering, Harbin University of Science and Technology, No. 52, Xuefu Rd, Harbin 150080, PR China;
Radiophysics and Electronics Department, Belarusian State University, Minsk 220030, Belarus;
nonstationary signal; rolling bearing; empirical mode decomposition; multi-class support vector machine; fault diagnosis;
机译:基于包络谱和支持向量机的滚动轴承故障分类。
机译:基于多尺度置换熵和改进支持向量机的二叉树滚动轴承故障诊断新方法
机译:使用支持向量机的转子轴承系统中的传感器不变式多类故障分类
机译:基于模糊c均值聚类和改进的多类最小二乘支持向量机的滚动轴承故障诊断。
机译:基于神经网络的旋转机械轴承故障分类:振动测量与功率测量的增强。
机译:时移多尺度模糊熵和拉普拉斯支持矢量机基滚动轴承故障诊断
机译:基于贝叶斯推断的多级支持向量机的可靠轴承故障诊断