ARENAS, Jorge P.. Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 51, n.4, p. 184-192, august 2017. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/sl/article/enhancing-the-vibration-signal-from-rolling-contact-bearing-using-an-adaptive-closed-loop-feedback-control-for-wavelet-de-noising/>. Date accessed: 16 apr. 2024. doi:http://dx.doi.org/.
Arenas, J. (2005). Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising. Strojniški vestnik - Journal of Mechanical Engineering, 51(4), 184-192. doi:http://dx.doi.org/
@article{.,
author = {Jorge P. Arenas},
title = {Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {51},
number = {4},
year = {2005},
keywords = {rolling contact bearings; vibration signals; noise analysis; feedback control; },
abstract = {Several techniques in both the time and frequency domains have been reported for the condition monitoring and fault diagnosis of equipment and processes. The monitoring and diagnosis is accomplished through the analysis and interpretation of signals acquired from sensors and transducers. However, any structure-borne vibration propagated through the neighbouring structures will produce a background vibration in which the required vibration signals for the diagnosis are often submerged, in particular during the early stage of failure development. If the background-noise level is too high or when the bearing vibration signature level is too low, traditional techniques such as wavelet de-noising analysis can be ineffective in cancelling the noise of such signals. In this paper the combination of an adaptive signal enhancement and the wavelet transform for denoising a vibration signal measured on a rolling contact bearing is presented. The normalized least meansquare and recursive least-square algorithms were used as the adaptive weight-control mechanism. The final aim of the adaptive filter was to minimize the mean-square value of the error signal, which implies the maximization of the output signal-to-noise ratio of the system. The results showed that a combination of the adaptive vibration signal enhancement and the wavelet transform yielded the best signal-to-noise ratio. This means that the result can reveal hidden signal structures that are directly associated with a bearings internal defect.},
issn = {0039-2480}, pages = {184-192}, doi = {},
url = {https://www.sv-jme.eu/sl/article/enhancing-the-vibration-signal-from-rolling-contact-bearing-using-an-adaptive-closed-loop-feedback-control-for-wavelet-de-noising/}
}
Arenas, J. 2005 August 51. Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 51:4
%A Arenas, Jorge P. %D 2005 %T Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising %B 2005 %9 rolling contact bearings; vibration signals; noise analysis; feedback control; %! Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising %K rolling contact bearings; vibration signals; noise analysis; feedback control; %X Several techniques in both the time and frequency domains have been reported for the condition monitoring and fault diagnosis of equipment and processes. The monitoring and diagnosis is accomplished through the analysis and interpretation of signals acquired from sensors and transducers. However, any structure-borne vibration propagated through the neighbouring structures will produce a background vibration in which the required vibration signals for the diagnosis are often submerged, in particular during the early stage of failure development. If the background-noise level is too high or when the bearing vibration signature level is too low, traditional techniques such as wavelet de-noising analysis can be ineffective in cancelling the noise of such signals. In this paper the combination of an adaptive signal enhancement and the wavelet transform for denoising a vibration signal measured on a rolling contact bearing is presented. The normalized least meansquare and recursive least-square algorithms were used as the adaptive weight-control mechanism. The final aim of the adaptive filter was to minimize the mean-square value of the error signal, which implies the maximization of the output signal-to-noise ratio of the system. The results showed that a combination of the adaptive vibration signal enhancement and the wavelet transform yielded the best signal-to-noise ratio. This means that the result can reveal hidden signal structures that are directly associated with a bearings internal defect. %U https://www.sv-jme.eu/sl/article/enhancing-the-vibration-signal-from-rolling-contact-bearing-using-an-adaptive-closed-loop-feedback-control-for-wavelet-de-noising/ %0 Journal Article %R %& 184 %P 9 %J Strojniški vestnik - Journal of Mechanical Engineering %V 51 %N 4 %@ 0039-2480 %8 2017-08-18 %7 2017-08-18
Arenas, Jorge. "Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising." Strojniški vestnik - Journal of Mechanical Engineering [Online], 51.4 (2005): 184-192. Web. 16 Apr. 2024
TY - JOUR AU - Arenas, Jorge P. PY - 2005 TI - Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising JF - Strojniški vestnik - Journal of Mechanical Engineering DO - KW - rolling contact bearings; vibration signals; noise analysis; feedback control; N2 - Several techniques in both the time and frequency domains have been reported for the condition monitoring and fault diagnosis of equipment and processes. The monitoring and diagnosis is accomplished through the analysis and interpretation of signals acquired from sensors and transducers. However, any structure-borne vibration propagated through the neighbouring structures will produce a background vibration in which the required vibration signals for the diagnosis are often submerged, in particular during the early stage of failure development. If the background-noise level is too high or when the bearing vibration signature level is too low, traditional techniques such as wavelet de-noising analysis can be ineffective in cancelling the noise of such signals. In this paper the combination of an adaptive signal enhancement and the wavelet transform for denoising a vibration signal measured on a rolling contact bearing is presented. The normalized least meansquare and recursive least-square algorithms were used as the adaptive weight-control mechanism. The final aim of the adaptive filter was to minimize the mean-square value of the error signal, which implies the maximization of the output signal-to-noise ratio of the system. The results showed that a combination of the adaptive vibration signal enhancement and the wavelet transform yielded the best signal-to-noise ratio. This means that the result can reveal hidden signal structures that are directly associated with a bearings internal defect. UR - https://www.sv-jme.eu/sl/article/enhancing-the-vibration-signal-from-rolling-contact-bearing-using-an-adaptive-closed-loop-feedback-control-for-wavelet-de-noising/
@article{{}{.},
author = {Arenas, J.},
title = {Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {51},
number = {4},
year = {2005},
doi = {},
url = {https://www.sv-jme.eu/sl/article/enhancing-the-vibration-signal-from-rolling-contact-bearing-using-an-adaptive-closed-loop-feedback-control-for-wavelet-de-noising/}
}
TY - JOUR AU - Arenas, Jorge P. PY - 2017/08/18 TI - Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 51, No 4 (2005): Strojniški vestnik - Journal of Mechanical Engineering DO - KW - rolling contact bearings, vibration signals, noise analysis, feedback control, N2 - Several techniques in both the time and frequency domains have been reported for the condition monitoring and fault diagnosis of equipment and processes. The monitoring and diagnosis is accomplished through the analysis and interpretation of signals acquired from sensors and transducers. However, any structure-borne vibration propagated through the neighbouring structures will produce a background vibration in which the required vibration signals for the diagnosis are often submerged, in particular during the early stage of failure development. If the background-noise level is too high or when the bearing vibration signature level is too low, traditional techniques such as wavelet de-noising analysis can be ineffective in cancelling the noise of such signals. In this paper the combination of an adaptive signal enhancement and the wavelet transform for denoising a vibration signal measured on a rolling contact bearing is presented. The normalized least meansquare and recursive least-square algorithms were used as the adaptive weight-control mechanism. The final aim of the adaptive filter was to minimize the mean-square value of the error signal, which implies the maximization of the output signal-to-noise ratio of the system. The results showed that a combination of the adaptive vibration signal enhancement and the wavelet transform yielded the best signal-to-noise ratio. This means that the result can reveal hidden signal structures that are directly associated with a bearings internal defect. UR - https://www.sv-jme.eu/sl/article/enhancing-the-vibration-signal-from-rolling-contact-bearing-using-an-adaptive-closed-loop-feedback-control-for-wavelet-de-noising/
Arenas, Jorge"Enhancing the Vibration Signal from Rolling Contact Bearing Using an Adaptive Closed-Loop Feedback Control for Wavelet De-Noising" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 51 Number 4 (18 August 2017)
Strojniški vestnik - Journal of Mechanical Engineering 51(2005)4, 184-192
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
Several techniques in both the time and frequency domains have been reported for the condition monitoring and fault diagnosis of equipment and processes. The monitoring and diagnosis is accomplished through the analysis and interpretation of signals acquired from sensors and transducers. However, any structure-borne vibration propagated through the neighbouring structures will produce a background vibration in which the required vibration signals for the diagnosis are often submerged, in particular during the early stage of failure development. If the background-noise level is too high or when the bearing vibration signature level is too low, traditional techniques such as wavelet de-noising analysis can be ineffective in cancelling the noise of such signals. In this paper the combination of an adaptive signal enhancement and the wavelet transform for denoising a vibration signal measured on a rolling contact bearing is presented. The normalized least meansquare and recursive least-square algorithms were used as the adaptive weight-control mechanism. The final aim of the adaptive filter was to minimize the mean-square value of the error signal, which implies the maximization of the output signal-to-noise ratio of the system. The results showed that a combination of the adaptive vibration signal enhancement and the wavelet transform yielded the best signal-to-noise ratio. This means that the result can reveal hidden signal structures that are directly associated with a bearings internal defect.