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首页> 外文期刊>IEEE Transactions on Instrumentation and Measurement >Hilbert–Huang Transform-Based Vibration Signal Analysis for Machine Health Monitoring
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Hilbert–Huang Transform-Based Vibration Signal Analysis for Machine Health Monitoring

机译:基于希尔伯特-黄变换的振动信号分析,用于机器健康监测

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This paper presents a signal analysis technique for machine health monitoring based on the Hilbert-Huang Transform (HHT). The HHT represents a time-dependent series in a two-dimensional (2-D) time-frequency domain by extracting instantaneous frequency components within the signal through an Empirical Mode Decomposition (EMD) process. The analytical background of the HHT is introduced, based on a synthetic analytic signal, and its effectiveness is experimentally evaluated using vibration signals measured on a test bearing. The results demonstrate that HHT is suited for capturing transient events in dynamic systems such as the propagation of structural defects in a rolling bearing, thus providing a viable signal processing tool for machine health monitoring
机译:本文提出了一种基于Hilbert-Huang变换(HHT)的用于机器健康监测的信号分析技术。 HHT通过经验模式分解(EMD)过程提取信号中的瞬时频率分量,从而代表了二维(2-D)时频域中随时间变化的序列。基于合成分析信号介绍了HHT的分析背景,并使用在测试轴承上测得的振动信号对HHT的有效性进行了实验评估。结果表明,HHT适用于捕获动态系统中的瞬态事件,例如滚动轴承中结构缺陷的传播,从而为监测机器健康提供了可行的信号处理工具

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