DEÁK, Krisztián ;MANKOVITS, Tamás ;KOCSIS, Imre . Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 63, n.1, p. 3-14, june 2018. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/article/optimal-wavelet-selection-for-the-size-estimation-of-manufacturing-defects-of-tapered-roller-bearings-with-vibration-measurement-using-shannon-entropy-criteria/>. Date accessed: 20 dec. 2024. doi:http://dx.doi.org/10.5545/sv-jme.2016.3989.
Deák, K., Mankovits, T., & Kocsis, I. (2017). Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria. Strojniški vestnik - Journal of Mechanical Engineering, 63(1), 3-14. doi:http://dx.doi.org/10.5545/sv-jme.2016.3989
@article{sv-jmesv-jme.2016.3989,
author = {Krisztián Deák and Tamás Mankovits and Imre Kocsis},
title = {Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {63},
number = {1},
year = {2017},
keywords = {condition monitoring; bearing vibration analysis; wavelet; entropy; dynamic model},
abstract = {Fault diagnosis of bearings is essential in manufacturing to increase quality. Traditionally, fault diagnosis of tapered roller element bearings is performed by signal processing methods, which handle the nonstationary behaviour of the signal. The wavelet transform is an efficient tool for analysing the vibration signal of the bearings because it can detect the sudden changes and transient impulses in the signal caused by faults in the bearing elements. In this article, manufacturing faults on the outer ring of tapered roller bearings due to the grinding process in manufacturing are investigated. Nine different real values wavelets (Symlet-2, Symlet-5, Symlet-8, db02, db06, db10, db14, Meyer, and Morlet) are compared according to the Energy-to-Shannon-Entropy ratio criteria, and which is efficient for detecting the manufacturing faults is determined. Finally, experiments are carried out on a test rig for determining the geometrical size of the manufacturing faults with all wavelets directly from the vibration signature the result of db02, Symlet-5, and Morlet wavelets are presented. When modelling the bearing structure as an under-damped second-order mass-spring-damper mechanical system, its unit impulse response function is compared to the wavelets on the basis of their Energy-to-Shannon-Entropy ratio to determine the fault size from the vibration signal. The proposed technique has been successfully implemented for measuring defect widths. The maximum deviation in result has been found to be 4.12 % for the defect width which was verified with image analysis methods using an optical microscope and contact measurement.},
issn = {0039-2480}, pages = {3-14}, doi = {10.5545/sv-jme.2016.3989},
url = {https://www.sv-jme.eu/article/optimal-wavelet-selection-for-the-size-estimation-of-manufacturing-defects-of-tapered-roller-bearings-with-vibration-measurement-using-shannon-entropy-criteria/}
}
Deák, K.,Mankovits, T.,Kocsis, I. 2017 June 63. Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 63:1
%A Deák, Krisztián %A Mankovits, Tamás %A Kocsis, Imre %D 2017 %T Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria %B 2017 %9 condition monitoring; bearing vibration analysis; wavelet; entropy; dynamic model %! Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria %K condition monitoring; bearing vibration analysis; wavelet; entropy; dynamic model %X Fault diagnosis of bearings is essential in manufacturing to increase quality. Traditionally, fault diagnosis of tapered roller element bearings is performed by signal processing methods, which handle the nonstationary behaviour of the signal. The wavelet transform is an efficient tool for analysing the vibration signal of the bearings because it can detect the sudden changes and transient impulses in the signal caused by faults in the bearing elements. In this article, manufacturing faults on the outer ring of tapered roller bearings due to the grinding process in manufacturing are investigated. Nine different real values wavelets (Symlet-2, Symlet-5, Symlet-8, db02, db06, db10, db14, Meyer, and Morlet) are compared according to the Energy-to-Shannon-Entropy ratio criteria, and which is efficient for detecting the manufacturing faults is determined. Finally, experiments are carried out on a test rig for determining the geometrical size of the manufacturing faults with all wavelets directly from the vibration signature the result of db02, Symlet-5, and Morlet wavelets are presented. When modelling the bearing structure as an under-damped second-order mass-spring-damper mechanical system, its unit impulse response function is compared to the wavelets on the basis of their Energy-to-Shannon-Entropy ratio to determine the fault size from the vibration signal. The proposed technique has been successfully implemented for measuring defect widths. The maximum deviation in result has been found to be 4.12 % for the defect width which was verified with image analysis methods using an optical microscope and contact measurement. %U https://www.sv-jme.eu/article/optimal-wavelet-selection-for-the-size-estimation-of-manufacturing-defects-of-tapered-roller-bearings-with-vibration-measurement-using-shannon-entropy-criteria/ %0 Journal Article %R 10.5545/sv-jme.2016.3989 %& 3 %P 12 %J Strojniški vestnik - Journal of Mechanical Engineering %V 63 %N 1 %@ 0039-2480 %8 2018-06-27 %7 2018-06-27
Deák, Krisztián, Tamás Mankovits, & Imre Kocsis. "Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria." Strojniški vestnik - Journal of Mechanical Engineering [Online], 63.1 (2017): 3-14. Web. 20 Dec. 2024
TY - JOUR AU - Deák, Krisztián AU - Mankovits, Tamás AU - Kocsis, Imre PY - 2017 TI - Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria JF - Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2016.3989 KW - condition monitoring; bearing vibration analysis; wavelet; entropy; dynamic model N2 - Fault diagnosis of bearings is essential in manufacturing to increase quality. Traditionally, fault diagnosis of tapered roller element bearings is performed by signal processing methods, which handle the nonstationary behaviour of the signal. The wavelet transform is an efficient tool for analysing the vibration signal of the bearings because it can detect the sudden changes and transient impulses in the signal caused by faults in the bearing elements. In this article, manufacturing faults on the outer ring of tapered roller bearings due to the grinding process in manufacturing are investigated. Nine different real values wavelets (Symlet-2, Symlet-5, Symlet-8, db02, db06, db10, db14, Meyer, and Morlet) are compared according to the Energy-to-Shannon-Entropy ratio criteria, and which is efficient for detecting the manufacturing faults is determined. Finally, experiments are carried out on a test rig for determining the geometrical size of the manufacturing faults with all wavelets directly from the vibration signature the result of db02, Symlet-5, and Morlet wavelets are presented. When modelling the bearing structure as an under-damped second-order mass-spring-damper mechanical system, its unit impulse response function is compared to the wavelets on the basis of their Energy-to-Shannon-Entropy ratio to determine the fault size from the vibration signal. The proposed technique has been successfully implemented for measuring defect widths. The maximum deviation in result has been found to be 4.12 % for the defect width which was verified with image analysis methods using an optical microscope and contact measurement. UR - https://www.sv-jme.eu/article/optimal-wavelet-selection-for-the-size-estimation-of-manufacturing-defects-of-tapered-roller-bearings-with-vibration-measurement-using-shannon-entropy-criteria/
@article{{sv-jme}{sv-jme.2016.3989},
author = {Deák, K., Mankovits, T., Kocsis, I.},
title = {Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {63},
number = {1},
year = {2017},
doi = {10.5545/sv-jme.2016.3989},
url = {https://www.sv-jme.eu/article/optimal-wavelet-selection-for-the-size-estimation-of-manufacturing-defects-of-tapered-roller-bearings-with-vibration-measurement-using-shannon-entropy-criteria/}
}
TY - JOUR AU - Deák, Krisztián AU - Mankovits, Tamás AU - Kocsis, Imre PY - 2018/06/27 TI - Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 63, No 1 (2017): Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2016.3989 KW - condition monitoring, bearing vibration analysis, wavelet, entropy, dynamic model N2 - Fault diagnosis of bearings is essential in manufacturing to increase quality. Traditionally, fault diagnosis of tapered roller element bearings is performed by signal processing methods, which handle the nonstationary behaviour of the signal. The wavelet transform is an efficient tool for analysing the vibration signal of the bearings because it can detect the sudden changes and transient impulses in the signal caused by faults in the bearing elements. In this article, manufacturing faults on the outer ring of tapered roller bearings due to the grinding process in manufacturing are investigated. Nine different real values wavelets (Symlet-2, Symlet-5, Symlet-8, db02, db06, db10, db14, Meyer, and Morlet) are compared according to the Energy-to-Shannon-Entropy ratio criteria, and which is efficient for detecting the manufacturing faults is determined. Finally, experiments are carried out on a test rig for determining the geometrical size of the manufacturing faults with all wavelets directly from the vibration signature the result of db02, Symlet-5, and Morlet wavelets are presented. When modelling the bearing structure as an under-damped second-order mass-spring-damper mechanical system, its unit impulse response function is compared to the wavelets on the basis of their Energy-to-Shannon-Entropy ratio to determine the fault size from the vibration signal. The proposed technique has been successfully implemented for measuring defect widths. The maximum deviation in result has been found to be 4.12 % for the defect width which was verified with image analysis methods using an optical microscope and contact measurement. UR - https://www.sv-jme.eu/article/optimal-wavelet-selection-for-the-size-estimation-of-manufacturing-defects-of-tapered-roller-bearings-with-vibration-measurement-using-shannon-entropy-criteria/
Deák, Krisztián, Mankovits, Tamás, AND Kocsis, Imre. "Optimal Wavelet Selection for the Size Estimation of Manufacturing Defects of Tapered Roller Bearings with Vibration Measurement using Shannon Entropy Criteria" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 63 Number 1 (27 June 2018)
Strojniški vestnik - Journal of Mechanical Engineering 63(2017)1, 3-14
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
Fault diagnosis of bearings is essential in manufacturing to increase quality. Traditionally, fault diagnosis of tapered roller element bearings is performed by signal processing methods, which handle the nonstationary behaviour of the signal. The wavelet transform is an efficient tool for analysing the vibration signal of the bearings because it can detect the sudden changes and transient impulses in the signal caused by faults in the bearing elements. In this article, manufacturing faults on the outer ring of tapered roller bearings due to the grinding process in manufacturing are investigated. Nine different real values wavelets (Symlet-2, Symlet-5, Symlet-8, db02, db06, db10, db14, Meyer, and Morlet) are compared according to the Energy-to-Shannon-Entropy ratio criteria, and which is efficient for detecting the manufacturing faults is determined. Finally, experiments are carried out on a test rig for determining the geometrical size of the manufacturing faults with all wavelets directly from the vibration signature the result of db02, Symlet-5, and Morlet wavelets are presented. When modelling the bearing structure as an under-damped second-order mass-spring-damper mechanical system, its unit impulse response function is compared to the wavelets on the basis of their Energy-to-Shannon-Entropy ratio to determine the fault size from the vibration signal. The proposed technique has been successfully implemented for measuring defect widths. The maximum deviation in result has been found to be 4.12 % for the defect width which was verified with image analysis methods using an optical microscope and contact measurement.