Defect Diagnosis and Modelling for A Rotating Machine Running at A Steady Pace

Year : 2025 | Volume : 13 | Special Issue 05 | Page : 154 164
    By

    Rajeev Kumar,

  • Ravi Kant Singh,

  • Ravi Shankar Rai,

  • Vikas Kumar,

  • Rakesh Dubey,

  • Subhash Gautam,

  1. Assistant Professor, Department of Mechanical Engineering, Sandip Institute of Technology and Research Centre, Nashik, Maharashtra, India
  2. Assistant Professor, Department of Mechanical Engineering, Sandip Institute of Technology and Research Centre, Nashik, Maharashtra, India
  3. Assistant Professor, Department of Automation and Robotics Engineering, Sandip Institute of Technology and Research Center, Nashik, Maharashtra, India
  4. Assistant Professor, Department of Automation and Robotics Engineering, Sandip Institute of Technology and Research Center, Nashik, Maharashtra, India
  5. Assistant Professor, Department of Mechanical Engineering, Sandip Institute of Technology and Research Centre, Nashik, Maharashtra, India
  6. Assistant Professor, Department of Mechanical Engineering, Sandip Institute of Technology and Research Centre, Nashik, Maharashtra, India

Abstract

Rotary equipment, such as gears, shafts, pumps, and bearings, are widely used across various rotary machine in industries, often operating under different loading conditions. The fluctuations in loading can lead to fatigue failures in rotating components, significantly affecting machinery performance. To investigate the behavior of such rotating equipment under diverse operational scenarios, a numerical model has been created. This approach can replace costly and often challenging experimental methods. However, it is essential that the model accurately reflects experimental results. The model’s complexity will vary based on the intended purpose of the simulation data. This paper presents dynamic models of a rolling contact ball bearing system and a single-stage spur gear transmission system. These models were created using ADAMS software, which simulates movement in multi-body systems. Both models are scalable, allowing for the introduction of any type of fault. In this study, the models are simulated under constant speed and constant load conditions, and the vibration response of the inner race, outer race, and ball in the case of the rolling contact ball bearing model, as well as the pinion and gear in the case of the gear dynamic model, are captured as vibrational signals. After that, the generated vibration signal is post-processed in MATLAB to evaluate the rotary machine’s condition, offering insights into its performance and potential issues. It is analyzed in both time and frequency domains to determine the machine’s overall state.

Keywords: Modelling, simulation, gear, bearing, time domain, Frequency domain.

[This article belongs to Special Issue under section in Journal of Polymer and Composites (jopc)]

aWQ6MjE3MTQ5fGZpbGVuYW1lOmVlY2U0YTMwLWZpLmF2aWZ8c2l6ZTp0aHVtYm5haWw=
How to cite this article:
Rajeev Kumar, Ravi Kant Singh, Ravi Shankar Rai, Vikas Kumar, Rakesh Dubey, Subhash Gautam. Defect Diagnosis and Modelling for A Rotating Machine Running at A Steady Pace. Journal of Polymer and Composites. 2025; 13(05):154-164.
How to cite this URL:
Rajeev Kumar, Ravi Kant Singh, Ravi Shankar Rai, Vikas Kumar, Rakesh Dubey, Subhash Gautam. Defect Diagnosis and Modelling for A Rotating Machine Running at A Steady Pace. Journal of Polymer and Composites. 2025; 13(05):154-164. Available from: https://journals.stmjournals.com/jopc/article=2025/view=217156


Browse Figures

References

  1. Daton I., Koren N., Klein R., Bortman J., A realistic dynamic model for gear fault diagnosis. Engineering Failure Analysis. 2018; 84: 77–100p.
  2. Sun R., Yang Z., Chen X., Tian S., Xie Y., Gear fault diagnosis based on the structured sparsity time-frequency analysis. Mechanical Systems and Signal Processing. 2018; 102: 346–363p.
  3. Tandon, N., Choudhury, A., A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribology international. 1999; 32: 469-480p.
  4. McFadden P. D., Smith J. D., Model for the vibration produced by a single point defect in a rolling element bearing. Journal of Sound and Vibration. 1984; 96: 69-82p.
  5. Mishra C., Samantaray A. K., Chakraborty G., Ball bearing defect models: A study of simulated and experimental fault signatures. Journal of sound and vibration. 2017; 400: 86-112p.
  6. Guo, Y., Parker, R. G., Dynamic modeling and analysis of a spur planetary gear involving tooth wedging and bearing clearance nonlinearity. European Journal of Mechanics-A/Solids. 2010; 29: 1022-1033p.
  7. Endo H., Randall R. B., Gosselin C., Differential diagnosis of spall vs. cracks in the gear tooth fillet region: Experimental validation. Mechanical Systems and Signal Processing. 2009; 23: 636–651p.
  8. Parey A., Badaoui M. E., Guillet F., Tandon N., Dynamic modelling of spur gear pair and application of empirical mode decomposition-based statistical analysis for early detection of localized tooth defect. Journal of Sound and Vibration. 2006; 294: 547–561p.
  9. Luo Y., Baddour N., Liang M., Dynamical modelling and experimental validation for tooth pitting and spalling in spur gears. Mechanical Systems and Signal Processing. 2019; 119: 155–181p.
  10. Chaari F., Baccar W., Abbes M. S., Haddar M., Effect of spalling or tooth breakage on gear mesh stiffness and dynamic response of a one-stage spur gear transmission. European Journal of Mechanics A/Solids. 2008; 27: 691–705p.
  11. Li F., Li R., Tian L., Chen L., Liu J., Data-driven time-frequency analysis method based on variational mode decomposition and its application to gear fault diagnosis in variable working conditions. Mechanical Systems and Signal Processing. 2019; 116: 462-479p.
  12. Kumar, R., Mitra, R.K., Dewangan, R., Mishra, C., Modelling and diagnosis of faults in simple bevel gear train. Wear. 2023; 524: 204881p.
  13. Kumar, R., Mandal, S., Mishra, C., Hui, N. B., Mitra, R. K., Defect Diagnosis of Bevel Gear System: A Study of Experimental and Simulated Signal. Journal of Sound and Vibration. 2024; 593: 118658p.
  14. Kumar, R., Mandal, S., Bhardwaj, P., Mishra, C., Mahato, S., Defect diagnosis of high contact ratio spur gear system with increasing level of fault. Engineering Failure Analysis. 2025: 169: 109097p.
  15. Kumar, R., Nanda, P., Mishra, C., Mitra, R. K., December. Modelling, Simulation and Defect Diagnosis of an Epi-cyclic Gear. In International Conference on Industrial Problems on Machines and Mechanism, Singapore: Springer Nature Singapore. 2022; 383-392p.
  16. Kumar, R., Mishra, C. and Mitra, R.K., December. Modeling and Diagnosis of High Contact Ratio Gear Faults. In Structural Integrity Conference and Exhibition, Singapore: Springer Nature Singapore. 2022; 631-645p.
  17. Ozguven H. N., Houser D. R., Dynamic analysis of high-speed gears by using loaded static transmission error. Journal of sound and vibration, 1988; 125: 71-83p.
  18. Saxena A., Parey A., Chouksey M., Time varying mesh stiffness calculation of spur gear pair considering sliding friction and spalling defects. Engineering Failure Analysis. 2016; 70: 200–211.
  19. Yavuz S. D., Saribay Z. B., Cigeroglu E., Nonlinear time-varying dynamic analysis of a spiral bevel geared system. Nonlinear Dynamics. 2018; 92: 1901–1919p.
  20. Chen Z., Zhai W., Shao Y., Wang K., Sun G., Analytical model for mesh stiffness calculation of spur gear pair with non-uniformly distributed tooth root crack. Engineering Failure Analysis. 2016; 66: 502–514p.
  21. Wang Q., Zhao B., Fu Y., Kong X., Ma H., An improved time-varying mesh stiffness model for helical gear pairs considering axial mesh force component. Mechanical Systems and Signal Processing. 2018; 106: 413–429p.
  22. Pandiyarajan R., Starvin M. S., Ganesh K. C., Contact Stress Distribution of Large Diameter Ball Bearing Using Hertzian Elliptical Contact Theory. Procedia Engineering. 2012; 38: 264 – 269.
Special Issue Subscription Original Research
Volume 13
Special Issue 05
Received 16/01/2025
Accepted 22/03/2025
Published 18/07/2025
Publication Time 183 Days
301

Login


My IP

PlumX Metrics