文件名称:Vibration-Monitoring
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The HHT represents a time-dependent series in
a two-dimensional (2-D) time-frequency domain by extracting
instan eous 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.-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.
a two-dimensional (2-D) time-frequency domain by extracting
instan eous 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.-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.
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Vibration Machine Health Monitoring.pdf