AYAD, Mouloud ;SAOUDI, Kamel ;REZKI, Mohamed ;BENZIANE, Mourad ;ARABI, Abderrazak . Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 68, n.1, p. 56-65, january 2022. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/article/early-detection-of-defects-in-gear-systems-using-autocorrelation-of-morlet-wavelet-transforms/>. Date accessed: 20 dec. 2024. doi:http://dx.doi.org/10.5545/sv-jme.2021.7384.
Ayad, M., Saoudi, K., Rezki, M., Benziane, M., & Arabi, A. (2022). Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms. Strojniški vestnik - Journal of Mechanical Engineering, 68(1), 56-65. doi:http://dx.doi.org/10.5545/sv-jme.2021.7384
@article{sv-jmesv-jme.2021.7384,
author = {Mouloud Ayad and Kamel Saoudi and Mohamed Rezki and Mourad Benziane and Abderrazak Arabi},
title = {Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {68},
number = {1},
year = {2022},
keywords = {Autocorrelation of Morlet Wavelet Transforms; early fault diagnosis; gear systems; vibration analysis; scalograms; },
abstract = {The supervision task of industrial systems is vital, and the prediction of damage avoids many problems. If any system defects are not detected in the early stage, this system will continue to degrade, which may cause serious economic loss. In industrial systems, the defects change the behaviour and characteristics of the vibration signal. This change is the signature of the presence of the defect. The challenge is the early detection of this signature. The difficulty of the vibration signal is that the signal is very noisy, non-stationary and non-linear. In this study, a new method for the early defect detection of a gear system is proposed. This approach is based on vibration analysis by finding the defect’s signature in the vibration signal. This approach has used the autocorrelation of Morlet wavelet transforms (AMWT). Firstly, simulation validation is introduced. The validation of the approach on a real system is given in the second validation part.},
issn = {0039-2480}, pages = {56-65}, doi = {10.5545/sv-jme.2021.7384},
url = {https://www.sv-jme.eu/article/early-detection-of-defects-in-gear-systems-using-autocorrelation-of-morlet-wavelet-transforms/}
}
Ayad, M.,Saoudi, K.,Rezki, M.,Benziane, M.,Arabi, A. 2022 January 68. Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 68:1
%A Ayad, Mouloud %A Saoudi, Kamel %A Rezki, Mohamed %A Benziane, Mourad %A Arabi, Abderrazak %D 2022 %T Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms %B 2022 %9 Autocorrelation of Morlet Wavelet Transforms; early fault diagnosis; gear systems; vibration analysis; scalograms; %! Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms %K Autocorrelation of Morlet Wavelet Transforms; early fault diagnosis; gear systems; vibration analysis; scalograms; %X The supervision task of industrial systems is vital, and the prediction of damage avoids many problems. If any system defects are not detected in the early stage, this system will continue to degrade, which may cause serious economic loss. In industrial systems, the defects change the behaviour and characteristics of the vibration signal. This change is the signature of the presence of the defect. The challenge is the early detection of this signature. The difficulty of the vibration signal is that the signal is very noisy, non-stationary and non-linear. In this study, a new method for the early defect detection of a gear system is proposed. This approach is based on vibration analysis by finding the defect’s signature in the vibration signal. This approach has used the autocorrelation of Morlet wavelet transforms (AMWT). Firstly, simulation validation is introduced. The validation of the approach on a real system is given in the second validation part. %U https://www.sv-jme.eu/article/early-detection-of-defects-in-gear-systems-using-autocorrelation-of-morlet-wavelet-transforms/ %0 Journal Article %R 10.5545/sv-jme.2021.7384 %& 56 %P 10 %J Strojniški vestnik - Journal of Mechanical Engineering %V 68 %N 1 %@ 0039-2480 %8 2022-01-20 %7 2022-01-20
Ayad, Mouloud, Kamel Saoudi, Mohamed Rezki, Mourad Benziane, & Abderrazak Arabi. "Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms." Strojniški vestnik - Journal of Mechanical Engineering [Online], 68.1 (2022): 56-65. Web. 20 Dec. 2024
TY - JOUR AU - Ayad, Mouloud AU - Saoudi, Kamel AU - Rezki, Mohamed AU - Benziane, Mourad AU - Arabi, Abderrazak PY - 2022 TI - Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms JF - Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2021.7384 KW - Autocorrelation of Morlet Wavelet Transforms; early fault diagnosis; gear systems; vibration analysis; scalograms; N2 - The supervision task of industrial systems is vital, and the prediction of damage avoids many problems. If any system defects are not detected in the early stage, this system will continue to degrade, which may cause serious economic loss. In industrial systems, the defects change the behaviour and characteristics of the vibration signal. This change is the signature of the presence of the defect. The challenge is the early detection of this signature. The difficulty of the vibration signal is that the signal is very noisy, non-stationary and non-linear. In this study, a new method for the early defect detection of a gear system is proposed. This approach is based on vibration analysis by finding the defect’s signature in the vibration signal. This approach has used the autocorrelation of Morlet wavelet transforms (AMWT). Firstly, simulation validation is introduced. The validation of the approach on a real system is given in the second validation part. UR - https://www.sv-jme.eu/article/early-detection-of-defects-in-gear-systems-using-autocorrelation-of-morlet-wavelet-transforms/
@article{{sv-jme}{sv-jme.2021.7384},
author = {Ayad, M., Saoudi, K., Rezki, M., Benziane, M., Arabi, A.},
title = {Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {68},
number = {1},
year = {2022},
doi = {10.5545/sv-jme.2021.7384},
url = {https://www.sv-jme.eu/article/early-detection-of-defects-in-gear-systems-using-autocorrelation-of-morlet-wavelet-transforms/}
}
TY - JOUR AU - Ayad, Mouloud AU - Saoudi, Kamel AU - Rezki, Mohamed AU - Benziane, Mourad AU - Arabi, Abderrazak PY - 2022/01/20 TI - Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 68, No 1 (2022): Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2021.7384 KW - Autocorrelation of Morlet Wavelet Transforms, early fault diagnosis, gear systems, vibration analysis, scalograms, N2 - The supervision task of industrial systems is vital, and the prediction of damage avoids many problems. If any system defects are not detected in the early stage, this system will continue to degrade, which may cause serious economic loss. In industrial systems, the defects change the behaviour and characteristics of the vibration signal. This change is the signature of the presence of the defect. The challenge is the early detection of this signature. The difficulty of the vibration signal is that the signal is very noisy, non-stationary and non-linear. In this study, a new method for the early defect detection of a gear system is proposed. This approach is based on vibration analysis by finding the defect’s signature in the vibration signal. This approach has used the autocorrelation of Morlet wavelet transforms (AMWT). Firstly, simulation validation is introduced. The validation of the approach on a real system is given in the second validation part. UR - https://www.sv-jme.eu/article/early-detection-of-defects-in-gear-systems-using-autocorrelation-of-morlet-wavelet-transforms/
Ayad, Mouloud, Saoudi, Kamel, Rezki, Mohamed, Benziane, Mourad, AND Arabi, Abderrazak. "Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 68 Number 1 (20 January 2022)
Strojniški vestnik - Journal of Mechanical Engineering 68(2022)1, 56-65
© The Authors 2022. CC BY 4.0 Int.
The supervision task of industrial systems is vital, and the prediction of damage avoids many problems. If any system defects are not detected in the early stage, this system will continue to degrade, which may cause serious economic loss. In industrial systems, the defects change the behaviour and characteristics of the vibration signal. This change is the signature of the presence of the defect. The challenge is the early detection of this signature. The difficulty of the vibration signal is that the signal is very noisy, non-stationary and non-linear. In this study, a new method for the early defect detection of a gear system is proposed. This approach is based on vibration analysis by finding the defect’s signature in the vibration signal. This approach has used the autocorrelation of Morlet wavelet transforms (AMWT). Firstly, simulation validation is introduced. The validation of the approach on a real system is given in the second validation part.