Dual-Core Denoised Synchrosqueezing Wavelet Transform for Gear Fault Detection

Yuan, Jing; Yao, Ze; Zhao, Qian; Xu, Yiyu; Li, Chao; Jiang, Huiming

doi:10.1109/tim.2021.3094838

Cited by 15 publications

(8 citation statements)

References 26 publications

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“…Finally, the experiment was repeated 10 times to obtain the average accuracy and running time as the final value. The accuracy of application experiment is shown in table 17.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

“…Jiang [16] proposed a sparse dictionary design based on cepstrum editing, which improved the accuracy of fault diagnosis. Yuan [17] combined cepstrum editing with empirical mode decomposition to accurately extract fault features under strong background noise. The above cepstrum based method is only applicable to the fault diagnosis under the condition of constant speed, and is invalid for the fault diagnosis under the condition of variable speed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Bearing fault diagnosis based on improved cepstrum under variable speed condition

Wang

Sun

2023

Eng. Res. Express

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The speed of rolling bearing often varies in actual operation process, the fault diagnosis of variable speed bearing is particularly important. In this paper, the deﬁnition of local maximum peak value of cepstrum is proposed, which can be used to extract variable speed features. And a variable speed bearing fault diagnosis method based on improved cepstrum is proposed. The proposed method could extract fault feature without tachometer and resampling. At ﬁrst, the Local maximum peaks of the original cepstrum are extracted. Then, the corresponding thresholds of the peaks are calculated and determined one by one. Finally, the feature extraction is completed according to the thresholds. At the same time, this paper veriﬁed the feature extraction results under four diﬀerent variable speed conditions, including acceleration, deceleration, acceleration before deceleration and deceleration before acceleration. The experiments results show that the proposed method has higher accuracy (99.08%) and less running time than the other spectral analysis methods, which demonstrates the accuracy, rapidity and eﬀectiveness. This proposed method provides a novel idea for fault diagnosis under condition of variable speed.

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“…Finally, the experiment was repeated 10 times to obtain the average accuracy and running time as the final value. The accuracy of application experiment is shown in table 17.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bearing fault diagnosis based on improved cepstrum under variable speed condition

Wang

Sun

2023

Eng. Res. Express

View full text Add to dashboard Cite

show abstract

“…In the CEM algorithm of this paper, the noise IMFs in the signal are filtered by the IMF correlation method, and there are also some other noise IMF filtering algorithms. Examples include the Hausdorff distance filter (HD) [27], the consecutive minimum square error filter (CMSE) [28], the selection criterion approach filter (SC) [29], the Energy Level filter (EL) [30], and so on. A comparative experiment was conducted to prove the superiority of the proposed method, and the experimental results are shown in Table 5.…”

Section: Resultsmentioning

confidence: 99%

Research of GPCEMBP Glucose Prediction Algorithm Based on Continuous Glucose Monitoring

Cai,

Ge,

Liu

2023

Journal of Sensors

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In view of the poor timeliness of dynamic blood glucose data and a delay of insulin effect for blood glucose control, and considering the nonlinearity and nonstationarity of the glucose data, a new blood Glucose Prediction algorithm combined Correlation coefficient-based complete ensemble empirical mode decomposition with adaptive noise and back propagation neural network (GPCEMBP) was proposed to increase the prediction time and improve the prediction accuracy. It refined the mode decomposition algorithm and integrated the correlation mode filter function to extract the characteristic intrinsic mode functions from the original signal. A new neural network prediction model was constructed by optimizing the number of hidden layer neurons, the number of hidden layers, activation functions, the number of inputs, structure, and other parameters. Finally, a predicted blood glucose value was calculated by phase space reconstruction technology. Through ablation and comparison experiments, it was demonstrated that the GPCEMBP algorithm had better prediction accuracy, convergence, and robustness in blood glucose prediction within 84 min. In addition, it has good adaptability to deal with different quality glucose data.

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“…Jiang et al [178] used a sparse dictionary design based on cepstrum editing, which improved the anti noise ability and the accuracy. Yuan et al [179] first used cepstrum editing method for the original signal, then used EMD for noise removal, and finally extracted the gearbox fault features from the time-frequency representation.…”

Section: Cepstrum Editingmentioning

confidence: 99%

Review of spectrum analysis in fault diagnosis for mechanical equipment

Wang,

Sun

2023

Eng. Res. Express

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Various mechanical equipment play a crucial role, and their health or status may affect efficiency and safety seriously. Spectrum analysis of the corresponding signal has been widely used to diagnose the fault in the past decades. The diagnosis method based on spectrum analysis technology covers almost all aspects of mechanical fault diagnosis. However, there is a lack of review of diagnostic methods of spectrum analysis technologies in the field of mechanical equipment fault diagnosis. In order to fill this gap, this paper reviews the spectrum analysis technology in mechanical equipment diagnosis in detail. First of all, in order to let the researchers who are in contact with spectrum analysis technology for the first time quickly understand this field, the principles of spectrum are systematically sorted out, including spectrum, cepstrum, energy spectrum, power spectrum, higher-order spectrum, Hilbert spectrum, marginal spectrum, envelope spectrum, singular spectrum and so on. Furthermore, the characteristics of corresponding spectrum analysis technologies are summarized, and their advantages and disadvantages are analyzed and compared. High-quality references in recent ten years are cited for illustration to enhance persuasiveness. Finally, the prospect of spectrum analysis technology is summarized, and the future development trend of spectrum analysis technology is pointed out. It is believed that the joint diagnosis of fault severity, variable speed fault diagnosis, combined with deep learning and multiple spectrum analysis technologies should be given more attention in the future. This paper is expected to provide a comprehensive overview of mechanical fault diagnosis based on spectrum analysis theory, and help to develop corresponding spectrum analysis technologies in practical engineering.

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Dual-Core Denoised Synchrosqueezing Wavelet Transform for Gear Fault Detection

Cited by 15 publications

References 26 publications

Bearing fault diagnosis based on improved cepstrum under variable speed condition

Bearing fault diagnosis based on improved cepstrum under variable speed condition

Research of GPCEMBP Glucose Prediction Algorithm Based on Continuous Glucose Monitoring

Review of spectrum analysis in fault diagnosis for mechanical equipment

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