Obtaining a Set of Vibrational Signals from Rolling Bearings with Varying Degrees of Local Defect Development in the Outer Ring

Introduction. The creation of reliable test sets of vibration signals remains a critical challenge in vibrodiagnostics, as the lack of data on early-stage bearing defects hinders the development and validation of diagnostic algorithms. Experimental acquisition of such signals is limited by the absence of appropriate test specimens and the long duration required for defect progression. Existing numerical simulation approaches demand high computational resources and complex setup, reducing their practical applicability. A significant gap in current research is the absence of a simple, reproducible, and validated methodology for generating signals that reflect the progressive development of defects. The objective of this study is to create a simplified methodology for generating a test set of bearing vibration signals that can be used to develop and verify new vibrodiagnostic techniques. The methodology is based on a combination of experimental and simulated signals.

Materials and Methods. Experimental data were obtained from a laboratory setup simulating a rotor unit with a rolling bearing (type 180603). To simulate early-stage defects (single and double chipping pits), dynamic finite element modelling was performed using ANSYS Mechanical (version 16.2) based on plane elements Plane162 using the LS-DYNA package. The resulting impulse sequences were superimposed onto the measured signal from a healthy bearing to generate combined signals. All signals (3 experimental, 2 combined) were analyzed using Fourier transform, bandpass filtering (5.4 kHz), and calculation of statistical parameters: root mean square (RMS), crest factor, and excess coefficient. Analysis was conducted in Mathcad (version 15.0).

Results. As a result of the study, a method for generating a test set of vibration signals from a rolling bearing was developed, covering the serviceable state and the sequential development of a local defect of the outer ring. The results showed a correlation between the amplitude of vibration signals and the stages of defects — an increase in amplitudes was observed in the high-frequency region, which confirmed the interaction of rolling elements and defective surfaces. Additional statistical analysis revealed an increase in diagnostic parameters (RMS value, crest factor, and excess coefficient) as the damage developed. It was found that the simulated signals reproduced the characteristic signs of a defect and fitted correctly into the general trend of parameter changes.

Discussion. The data obtained demonstrate that the proposed technique makes it possible to simplify the generation of reference signals without the need for long-term accumulation of experimental data or damage to equipment. The physical validity of the simulated pulses and the consistency of growth dynamics of diagnostic parameters with real data confirm the possibility of using this method for standardized testing of vibrodiagnostic techniques.

Conclusion. The developed methodology provides an efficient and reproducible approach to generating test signal sets for vibrodiagnostics. It can be used to accelerate algorithm verification, reduce experimental costs, and improve diagnostic reliability. Future research will focus on simplifying impulse generation through analytical modelling and extending the methodology to other bearing types and defect forms.

1. Nguyen Duc Thuan, Hoang Si Hong. HUST Bearing: A Practical Dataset for Ball Bearing Fault Diagnosis. arXiv. 2023. https://doi.org/10.48550/arXiv.2302.12533

2. Jing Liu, Yimin Shao. A New Dynamic Model for Vibration Analysis of a Ball Bearing due to a Localized Surface Defect Considering Edge Topographies. Nonlinear Dynamics. 2015;79:1329–1351. https://doi.org/10.1007/s11071-014-1745-y

3. Halmos F, Wartzack S, Bartz M. Investigation of Failure Mechanisms in Oil-Lubricated Rolling Bearings under Small Oscillating Movements: Experimental Results, Analysis and Comparison with Theoretical Models. Lubricants. 2024;12(8):271. https://doi.org/10.3390/lubricants12080271

4. Jain PH, Bhosle SP. Mathematical Modeling, Simulation and Analysis of Non-Linear Vibrations of a Ball Bearing due to Radial Clearance and Number of Balls. Materials Today: Proceedings. 2023;72(3):927–936. https://doi.org/10.1016/j.matpr.2022.09.093

5. Menck O. The Finite Segment Method–A Numerical Rolling Contact Fatigue Life Model for Bearings Subjected to Stochastic Operating Conditions. ASME Journal of Tribology. 2023;145(3):031201. https://doi.org/10.1115/1.4055916

6. Wrzochal M, Adamczak S. The Problems of Mathematical Modelling of Rolling Bearing Vibrations. Bulletin of the Polish Academy of Sciences: Technical Sciences. 2020;68(6):1363–1372. https://doi.org/10.24425/bpasts.2020.135398

7. Lihai Chen, Ao Tan, Lixiu Yang, Xiaoxu Pang, Ming Qiu. Defect Size Evaluation of Cylindrical Roller Bearings with Compound Faults on the Inner and Outer Races. Mathematical Problems in Engineering. 2022;2022(2):1–12. https://doi.org/10.1155/2022/6070822

8. Malanchuk Y, Moshynskyi V, Korniienko V, Malanchuk Z. Modeling the Process of Hydromechanical Amber Extraction. E3S Web of Conferences. 2018;60:00005. https://doi.org/10.1051/e3sconf/20186000005

9. Ali Safian, Hongsheng Zhang, Xihui Liang, Nan Wu. Dynamic Simulation of a Cylindrical Roller Bearing with a Local Defect by Combining Finite Element and Lumped Parameter Models. Measurement Science and Technology. 2021;32(12):125111. https://doi.org/10.1088/1361-6501/ac2317

10. Tianhe Wang, Lei Chen, Hong Lu, Shaojun Wang, Zhangjie Li, Wei Zhang, et al. Finite Element Dynamic Model and Vibration Signal Simulation of Rolling Bearing with Local Faults. In: Proc. 18th International Manufacturing Science and Engineering Conference. New York NY: ASME. 2023;2:105504. https://doi.org/10.1115/MSEC2023-105504

11. Gururaj Upadhyaya, Kumar HS. A Comparative Study of Statistical Features Used in Rolling Element Bearing Health Diagnosis Using Six Sigma Approach. In: Proc. 2nd Indian International Conference on Industrial Engineering and Operations Management. Southfield, MI: IEOM Society International; 2022. https://doi.org/10.46254/IN02.20220244

12. Jain PH, Bhosle SP. Study of Effects of Radial Load on Vibration of Bearing Using Time-Domain Statistical Parameters. IOP Conference Series: Materials Science and Engineering. 2021;1070:012130. https://doi.org/10.1088/1757-899X/1070/1/012130

13. Trufanov NN, Churikov DV, Kravchenko OV. Application of Spectral Analysis Methods for Data Pre-processing of Anomaly Detection Problem of Vibration Diagnostics in Non-destructive Testing. Journal of Physics: Conference Series. 2021;2127:012028. https://doi.org/10.1088/1742-6596/2127/1/012028

14. Garad A, Sutar KB, Shinde VJ, Pawar AC. Analysis of Vibration Signals of Rolling Element Bearing with Localized Defects. International Journal of Current Engineering and Technology. 2017;7:37–42.

15. Tetter V, Tetter A, Denisova I. Researching the Possibility of Determining the Technical Condition of Rolling Bearings by the Kurtosis Factor. In: Proc. International Russian Automation Conference (RusAutoCon). New York City: IEEE; 2023. P. 149–153. https://doi.org/10.1109/RusAutoCon58002.2023.10272799

16. Puzyr V, Mykhalkiv S. Classification of the Technical Condition of Rolling Bearing by the Scalar Indicators and Support Vector Machines. Progresivna tehnìka, tehnologìâ ta ìnženerna osvìta. 2023.