Application of vibration signal analysis method in the fault diagnosis of mechanical gearboxes
More details
Hide details
1
Xinxiang Vocational and Technical College, Xinxiang 453006, China
Submission date: 2024-08-14
Final revision date: 2024-12-20
Acceptance date: 2025-01-09
Online publication date: 2025-01-29
Publication date: 2025-01-29
Corresponding author
Jincui Liu
Xinxiang Vocational and Technical College, Xinxiang 453006
KEYWORDS
TOPICS
ABSTRACT
The traditional mechanical gearbox diagnosis method is not enough to meet the operation requirements in terms of reliability and safety, so the purpose of this study is to collect and analyze the vibration signal of mechanical gearbox, and explore the application of vibration signal analysis method in fault diagnosis. A vibration sensor is installed in a gear box to collect real-time vibration data, and the data are denoised, filtered and aligned. The experimental results show that the waveform of the normal gear has obvious periodicity, while the high-frequency component of the faulty gear increases significantly. The diagnostic accuracy of fault types is wear, pitting, point wear, fracture wear and broken teeth. The envelope spectrum amplitude of normal bearings is maintained between 0.4-0.5. The innovation of the research lies in the development of a fault signal acquisition system based on advanced vibration sensing technology, which realizes real-time monitoring of gearbox status and accurate collection of vibration data, and optimizes the ability to extract fault characteristics from complex background noise by combining a variety of vibration signal processing technologies.
FUNDING
This research received no external funding.
REFERENCES (22)
1.
Yu J, Song YR, Zhang HS, Dong XH. Novel design of compound coupled hydro-mechanical transmission on heavy-duty vehicle for energy recycling. Energy. 2022; 239(5):654-671.
https://doi.org/10.1016/j.ener....
2.
Mastrone MN, Concli F. CFD simulation of grease lubrication: analysis of the power losses and lubricant flows inside a back-to-back test rig gearbox. Journal of Non-Newtonian Fluid Mechanics. 2021;297:3(21): 104-121.
https://doi.org/10.1016/j.jnnf....
3.
Mastrone MN, Hartono EA, Cheernoray V, Concli F. Oil distribution and churning losses of gearboxes: experimental and numerical analysis. Tribology International. 2020;151(1):219-232.
https://doi.org/10.1016/j.trib....
4.
He XZ, Zhou XQ, Yu WN, Hou YX, Mechefske CK. Adaptive variational mode decomposition and its application to multi-fault detection using mechanical vibration signals. ISA Transactions. 2020;111(4):234-248, 2020.
https://doi.org/10.1016/j.isat....
5.
Li YC, Sun W, Han YQ. Signal-segments cross-coherence method for nonlinear structural damage detection using free-vibration signals. Advances in Structural Engineering. 2020;23(6):1041-1054.
https://doi.org/10.1177/136943....
6.
Feng JJ, Men Y, Zhu GJ, Li YZ, Luo XG. Cavitation detection in a Kaplan turbine based on multifractal detrended fluctuation analysis of vibration signals. Ocean Engineering. 2022;263(1):963-970.
https://doi.org/10.1016/j.ocea....
7.
Miao M, Sun Y, Yu J. Deep sparse representation network for feature learning of vibration signals and its application in gearbox fault diagnosis. Knowledge-Based Systems. 2022;240(2):108-116.
https://doi.org/10.1016/j.know... Syst.2022.122276.
8.
Ouyang T, Wang J, Mo X, Li Y. Vibration and cavitation in high-speed gears caused by faults. International Journal of Mechanical Sciences. 2023;2(2):12-23.
https://doi.org/10.1016/j.intj....
9.
Wang J, Hui M, Liu B, Wang X, Yang J. Machining process monitoring with vibration signal based manifold learning. The Journal of the Acoustical Society of America. 2020;148(4):2766-2766.
https://doi.org/10.1016/jasa.2....
10.
Ma C, Zhao D, Sun W, Liao W, Xiao Y, He X. Nonlinear dynamic mechanical response analysis of dual-segment single-span rotor-bearing system under normal condition and misalignment fault. Archive of Applied Mechanics. 2023;7(11):675-687.
https://doi.org/10.1016/aam.20....
11.
Casamenti E, Yang T, Vlugter P, Bellouard Y. Vibration monitoring based on optical sensing of mechanical nonlinearities in glass suspended waveguides. Optics Express. 2021;29(7):10853-10862.
https://doi.org/10.1016/optexp....
12.
Wang S, Zhu R, Xiao Z. Investigation on crack failure of helical gear system of the gearbox in wind turbine: Mesh stiffness calculation and vibration characteristics recognition. Ocean engineering. 2022;15(4):250-263.
https://doi.org/10.1016/oceeng....
13.
Chu C, Ge Y, Qian Q, Hua B, Guo J. A novel multi-scale convolution model based on multi-dilation rates and multi-attention mechanism for mechanical fault diagnosis. Digital Signal Processing. 2022;7(1):43-56.
https://doi.org/10.1016/digsp.....
14.
Li X, Zhong X, Shao H, Han T, Shen C. Multi-sensor gearbox fault diagnosis by using feature-fusion covariance matrix and multi-Riemannian kernel ridge regression. Reliability Engineering and System Safety, 2021;9(1):216-225.
https://doi.org/10.1016/ress.2....
15.
Xiang B, Luo JH, Gao L. Protection schemes using resistive-type superconducting fault current limiters with mechanical DC circuit breakers in MMC-MTDC grids. IET Generation Transmission & Distribution. 2020;14(1):3422-3432.
https://doi.org/10.1049/iet-gt....
16.
Yuan Y, Zhao J, Hong K, Wang N, Zheng J. Assessment of the winding mechanical condition based on transformer vibration during transient processes. Electronics. 2024;13(1):2519-2519.
https://doi.org/10.3390/electr....
17.
Jawad SM, Jaber AA. Bearings health monitoring based on frequency-domain vibration signals analysis. Engineering and Technology Journal. 2023;41(1): 86-95.
https://doi.org/10.30684/etj.2....
18.
Duan CQ, Li YF, Pu HY, Luo Y. Adaptive monitoring scheme of stochastically failing systems under hidden degradation processes. Reliability Engineering and System Safety. 2022;221(2):267-289.
https://doi.org/10.1016/j.ress....
19.
Gyftakis K, Panagiotou P, Spyrakis D. Detection of simultaneous mechanical faults in 6 kV pumping induction motors using combined MCSA and stray flux methods. IET Electric Power Applications. 2020; 15(5):64-652.
https://doi.org/10.1049/elp2.1....
20.
John YM, Sanusi A, Yusuf I. Reliability analysis of multi-hardware-software system with failure interaction. Journal of Computational and Cognitive Engineering. 2023;2(1):38-46.
https://doi.org/10.47852/bonvi....
21.
Huang P, Gu Y, Qiu G. A novel feature dimensionality reduction method for gearbox fault diagnosis with HMSDE, DANCo-DDMA and KELM. Nonlinear Dynamics. 2024;112(1):14071-14091.
https://doi.org/10.1007/s11071....
22.
Touti W, Salah M, Sheng S, Bacha K. An envelope time synchronous averaging for wind turbine gearbox fault diagnosis. Journal of Vibration Engineering & Technologies. 2024;12(4):6513-6525.
https://doi.org/10.1007/s42417....