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机译:改善用于异常检测和分类的单变量控制图的性能
Dynamics and Structures Laboratory, Machine Design and Control Systems Section, School of Mechanical Engineering, National Technical University of Athens, Athens, Greece;
Dynamics and Structures Laboratory, Machine Design and Control Systems Section, School of Mechanical Engineering, National Technical University of Athens, Athens, Greece;
KU Leuven, Department of Mechanical Engineering, Division PMA, Celestijnenlaan 300, BOX 2420, Leuven 3001, Belgium,Flanders Make, Belgium;
Dynamics and Structures Laboratory, Machine Design and Control Systems Section, School of Mechanical Engineering, National Technical University of Athens, Athens, Greece;
Novelty detection; Bearing fault diagnosis; Feature extraction; Control charts; Morphological gradients; Morlet wavelet;
机译:使用统计参数和单变量统计过程控制图检测正齿轮系统中的齿轮磨损和故障
机译:多层感知器的异常控制图模式分类优化
机译:多层感知器的异常控制图模式分类优化
机译:统计控制图和神经网络分类可改善人体跌倒检测
机译:使用多变量统计质量控制图的分析以及基于底层差异和协方差的效果的T2多变量质量控制图的多变量过程
机译:死亡率控制图可改善对手术性能的监测
机译:故障检测和诊断,通过改进的单变量统计过程控制图进行FDD,USPC
机译:提高自适应/响应信号控制对非侵入式检测和传统时序的性能影响。