Abstract
The Synchrosqueezing is a special case of the reassignment method and concentrates the time-frequency representation (TFR) in a scale dimension. Compared to other TFR enhancement methods, the synchrosqueezing offers better adaptability, less deformation for IF profile and an exact reconstruction formula for constituent components. This paper deals with the investigation of descriptors based on the combination of the synchrosqueezing transform (SST) and Lempel-Ziv complexity methods. This last one transforms the analyzed signal into a data sequence. In the first part, the vibration signal components are extracted by using the synchrosqueezing transform and the reconstruction method. Afterward, the Lempel-Ziv complexity values are calculated. Since the complexity values are not dependent on the magnitude of the measured signal, the proposed method is less sensitive to the data sets measured under different data acquisition conditions. This approach is applied for monitoring and diagnosing the defects during a fatigue test on a first gear reducer and also when varying the load on a second gear reducer by using the recorded vibration signals. It can also provide a new way for feature extraction and recognition of gear system faults.
Highlights
As announced in Daubechies et al [8], the synchrosqueezing transform (SST) method can be used as a method to decompose a vibration signal like the empirical mode decomposition (EMD) method [14,15]; we propose to benefit from this advantage to diagnose gear faults
This study presents an investigation of the Synchrosqueezing method and the Normalized Complexity for monitoring the gear fault evolution
This method is applied to vibration data obtained from two experimental tests; fatigue test conducted by CETIM (France) during 12 days and Peter Rig conducted by the UNWK (Australia)
Summary
Posing them into different components and instead make use of the TF analysis provided by the SST method. The first part gives a thorough discussion of the TFRs, and their properties, providing all the information that is needed to understand and apply them effectively the procedure to use the SST method like EMD to decompose a multicomponent signal are exposed. It is important to know that ridge reconstruction appears to be more robust to interference and noise, while direct reconstruction performs better in the case of considerable amplitude/frequency modulation [18]. This is quite understandable, since, as we saw, the AM/FM components can be represented as a sum of tones with particular amplitude, phase and frequency relationships, so the amplitude and frequency modulation can be viewed as arising due to interference between these AM/FM induced tones
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