High-order synchrosqueezing wavelet transform and application to planetary gearbox fault diagnosis

Hu, Yue; Tu, Xiaotong

doi:10.1016/j.ymssp.2019.05.050

Cited by 96 publications

(26 citation statements)

References 25 publications

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“…Hu et al [36] proposed a time-frequency method based on the highorder SST and a multitaper empirical wavelet transform (MTEWT) for a wind turbine planetary gearbox under nonstationary conditions. ey also proposed a high-order synchrosqueezing wavelet transform and applied it to planetary gearbox fault diagnosis under variable operating conditions [37]. Lu et al [38] and Fei et al [39] proposed the multifeature entropy distance for the process characteristic analysis and diagnosis of rolling bearing faults by the integration of four information entropies in the time, frequency, and TF domains and two kinds of signals: vibration signals and acoustic emission signals.…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Version of Second‐Order Synchrosqueezing Transform Combined with Time‐Frequency Image Texture Features to Detect Faults in Bearings

Cheng

Wang

et al. 2021

Shock and Vibration

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Signals with multiple components and fast-varying instantaneous frequencies reduce the readability of the time-frequency representations obtained by traditional synchrosqueezing transforms due to time-frequency blurring. We discussed a vertical synchrosqueezing transform, which is a second-order synchrosqueezing transform based on the short-time Fourier transform and compared it to the traditional short-time Fourier transform, synchrosqueezing transform, and another form of the second-order synchrosqueezing transform, the oblique synchrosqueezing transform. The quality of the time-frequency representation and the accuracy of mode reconstruction were compared through simulations and experiments. Results reveal that the second-order frequency estimator of the vertical synchrosqueezing transform could obtain accurate estimates of the instantaneous frequency and achieve highly energy-concentrated time-frequency representations for multicomponent and fast-varying signals. We also explored the application of statistical feature parameters of time-frequency image textures for the early fault diagnosis of roller bearings under fast-varying working conditions, both with and without noise. Experiments showed that there was no direct positive correlation between the resolution of the time-frequency images and the accuracy of fault diagnosis. However, the early fault diagnosis of roller bearings based on statistical texture features of high-resolution images obtained by the vertical synchrosqueezing transform was shown to have high accuracy and strong robustness to noise, thus meeting the demand for intelligent fault diagnosis.

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Section: Introductionmentioning

confidence: 99%

An Enhanced Version of Second‐Order Synchrosqueezing Transform Combined with Time‐Frequency Image Texture Features to Detect Faults in Bearings

Cheng

Wang

et al. 2021

Shock and Vibration

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“…19,20 To deal with the shortcomings of SST and to achieve high spectral resolution, various concentrated SST methods such as generalized SST, demodulated SST, multitapered SST, and higher-order SST have been proposed. [21][22][23][24][25] The SST-based methods successfully applied in many fields of engineering, such as studies related to machine fault diagnosis, seismic signal analysis, and gravitational waves. 24,25 Yu et al 26 proposed an ideal TFA method called as synchroextracting transform (SET) to analyze nonstationary time series data.…”

Section: Introductionmentioning

confidence: 99%

Nonstationary waveform detection in power quality signals using multisynchrosqueezing transform

Sahu¹,

Dash

2021

Int Trans Electr Energ Syst

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Time-frequency (TF) analysis (TFA) is widely used as a reliable signalprocessing tool for the detection and identification of time-varying waveforms in power quality (PQ) signals. However, the effectiveness of a TFA method is limited by Heisenberg uncertainty principle. The presence of cross terms is also a significant issue in TF analysis of real-time signals. In PQ signal analysis, it is highly necessary to apply a suitable TFA technique with higher clarity and fewer cross-term problems. This paper introduces a newly developed TFA method known as multisynchrosqueezing transform (MSST) to detect the presence of nonstationary waveforms in PQ disturbance signals. The MSST is a high-resolution TFA method, which is similar to synchrosqueezing transform (SST) but has an iterative reassignment process to enhance the energy concentration of the TF representation. We apply the MSST to various types of single and combined PQ disturbance signals and show its potential application to PQ disturbance signal analysis. Results show that MSST provides higher TF resolution compared to other contemporary methods.

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“…The high-order SST (HSST) was proposed for IF estimation [ 14 ]. However, the computation cost is very high due to the high-order approximation of the FM function.…”

Section: Introductionmentioning

confidence: 99%

Novel Method for Vibration Sensor-Based Instantaneous Defect Frequency Estimation for Rolling Bearings Under Non-Stationary Conditions

Zhao

Gelman

Chu

et al. 2020

Sensors

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It is proposed a novel instantaneous frequency estimation technology, multi-generalized demodulation transform, for non-stationary signals, whose true time variations of instantaneous frequencies are unknown and difficult to extract from the time-frequency representation due to essentially noisy environment. Theoretical bases of the novel instantaneous frequency estimation technology are created. The main innovations are summarized as: (a) novel instantaneous frequency estimation technology, multi-generalized demodulation transform, is proposed, (b) novel instantaneous frequency estimation results, obtained by simulation, for four types of amplitude and frequency modulated non-stationary single and multicomponent signals under strong background noise (signal to noise ratio is −5 dB), and (c) novel experimental instantaneous frequency estimation results for defect frequency of rolling bearings for multiple defect frequency harmonics, using the proposed technology in non-stationary conditions and in conditions of different levels of noise interference, including a strong noise interference. Quantitative instantaneous frequency estimation errors are employed to evaluate performance of the proposed IF estimation technology. Simulation and experimental estimation results show high effectiveness of the proposed estimation technology.

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High-order synchrosqueezing wavelet transform and application to planetary gearbox fault diagnosis

Cited by 96 publications

References 25 publications

An Enhanced Version of Second‐Order Synchrosqueezing Transform Combined with Time‐Frequency Image Texture Features to Detect Faults in Bearings

An Enhanced Version of Second‐Order Synchrosqueezing Transform Combined with Time‐Frequency Image Texture Features to Detect Faults in Bearings

Nonstationary waveform detection in power quality signals using multisynchrosqueezing transform

Novel Method for Vibration Sensor-Based Instantaneous Defect Frequency Estimation for Rolling Bearings Under Non-Stationary Conditions

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