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机译:使用稀疏过完备特征的智能状态监测方法,用于从高度压缩的测量中获取轴承故障
Department of Electronic and Computer Engineering, Brunei University London, Uxbridge UB8 3PH, United Kingdom;
Heriot-Watt University Malaysia, Precinct 5, 62200 Putrajaya, Malaysia;
Department of Electronic and Computer Engineering, Brunei University London, Uxbridge UB8 3PH, United Kingdom,The Key Laboratory of Embedded Systems and Service Computing, College of Electronic and Information Engineering, Tongji University, Shanghai, China;
Compressed sensing; Sparse over-complete representations; Deep neural network; Sparse autoencoder; Bearing fault classification; Machine condition monitoring;
机译:基于压缩检测的稀疏自动编码方法和小波包能量熵,用于滚动轴承智能故障诊断
机译:智能诊断滚动轴承复合故障基于设备状态词典集稀疏分解特征提取 - 隐藏马尔可夫模型
机译:基于稀疏测量矩阵的轴承故障信号的特征增强方法
机译:振动,轴承健康和温度测量的滚动/滚珠轴承状态监测和单个传感器的共振方法
机译:振动测量,齿轮故障检测和轴承故障检测的改进方法,用于齿轮箱诊断。
机译:轴承状况监测中基于块稀疏贝叶斯学习的压缩感知重构
机译:智能诊断滚动轴承复合故障基于设备状态词典集稀疏分解特征提取 - 隐藏马尔可夫模型