Analysis of the application of vibration diagnostics and thermography methods for an early detection of defects in an industrial mixer-gearbox system – a case study

Keywords: planetary gearbox, industrial mixer, vibrodiagnostic, thermograpfic, analysis, bearing, reliability, maintenance

Abstract


Introduction/purpose:Bearings constitute essential components without which the functioning of systems subject to significant loads would be inconceivable. The bearing installation process in rotational systems diligently influences their longevity, reliability, and efficiency. Accurate and meticulous bearing installation is of paramount importance to ensure optimal operational performance of rotational systems. Proper bearing assembly assists in the even distribution of loads, reduction of friction, and minimization of wear. Additionally, appropriately mounted bearings decrease the risk of vibrations, noise, and potential system failures. Therefore, the bearing installation process represents a crucial step in maintaining the reliable and efficient operation of rotational systems, thereby extending their operational lifespan and reducing the need for repairs.

Methods: The methodology employed in this study combines vibrodiagnostic analysis of an industrial mixer equipped with a planetary gearbox and the concurrent application of thermographic techniques. This integrated approach provides a comprehensive understanding of the system's condition and helps identify potential sources of heating within both the gearbox and the mixer. Vibrodiagnostic examinations encompassed the analysis of vibrations generated by the planetary gearbox during its operation, coupled with the interpretative scrutiny of results aimed at detecting possible imbalances, damages, or irregularities within the mechanical system. On the other hand, the application of thermography contributed to generating a visual representation of temperature distributions at critical points of the gearbox, facilitating the identification of thermal anomalies. The integration of these methods enables a holistic scientific approach to the analysis of the planetary gearbox system, allowing for detailed diagnostics and an understanding of the root causes of potential operational issues in the gearbox.

Results:The meticulous interpretation of acquired data facilitated the identification of potential causes of thermal loading in the planetary gearbox, providing a comprehensive insight into the mechanical and thermal facets of the entire system. The integration of vibrodiagnostic and thermograpfic methods constitutes a pivotal component of a holistic analytical approach, crucial for an exhaustive understanding of the performance and overall condition of the planetary gearbox and industrial mixer. The obtained results serve as the foundation for the development of precise diagnostic procedures, laying the groundwork for the implementation of pertinent improvements or maintenance strategies within the system. This, in turn, holds the potential to optimize the operational performance of the planetary gearbox and extend its operational lifespan.

Conclusion: The applied methodology, based on vibrodiagnostic analyses and thermographic techniques, has provided a comprehensive insight into the condition of both the planetary gearbox and the industrial mixer containing it, with all analyses described in the text conducted on each component within the mixer system. The detailed interpretation of data has enabled the identification of potential causes of gearbox heating, offering a deeper understanding of the mechanical and thermal aspects of the system. In this manner, the efficiency of maintaining the examined system can be enhanced.

References

Aherwar, A. (2012). An investigation on gearbox fault detection using vibration analysis techniques: A review. Australian Journal of Mechanical Engineering, 10(2), 169–183. https://doi.org/10.7158/M11-830.2012.10.2

Batinic, V. J. (2013). Planetary gear dynamic response to mesh. Vojnotehnički Glasnik, 61(1), 58–68. 10.5937/vojtehg61-2006

Chatterjee, J., & Dethlefs, N. (2021). Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future. Renewable and Sustainable Energy Reviews, 144, 111051. https://doi.org/10.1016/j.rser.2021.111051

Cheng, Z., Hu, N., & Zhang, X. (2012). Crack level estimation approach for planetary gearbox based on simulation signal and GRA. Journal of Sound and Vibration, 331(26), 5853–5863. https://doi.org/10.1016/j.jsv.2012.07.035

De Silva, C. W. (2007). Vibration monitoring, testing, and instrumentation. CRC Press. DOI: 10.1201/9781420053203

Gawde, S., Patil, S., Kumar, S., & Kotecha, K. (2023). A scoping review on multi-fault diagnosis of industrial rotating machines using multi-sensor data fusion. Artificial Intelligence Review, 56(5), 4711–4764. https://doi.org/10.1007/s10462-022-10243-z

Goyal, D., & Pabla, B. (2016). The vibration monitoring methods and signal processing techniques for structural health monitoring: A review. Archives of Computational Methods in Engineering, 23, 585–594. 10.1007/s11831-015-9145-0

Guo, Y., & Parker, R. G. (2011). Analytical determination of mesh phase relations in general compound planetary gears. Mechanism and Machine Theory, 46(12), 1869–1887. https://doi.org/10.1016/j.mechmachtheory.2011.07.010

Jakubek, B., Grochalski, K., Rukat, W., & Sokol, H. (2022). Thermovision measurements of rolling bearings. Measurement, 189, 110512. 10.1016/j.measurement.2021.110512

Lei, Y., Han, D., Lin, J., & He, Z. (2013). Planetary gearbox fault diagnosis using an adaptive stochastic resonance method. Mechanical Systems and Signal Processing, 38(1), 113–124. 10.1016/j.ymssp.2012.06.021

Lei, Y., Zuo, M. J., He, Z., & Zi, Y. (2010). A multidimensional hybrid intelligent method for gear fault diagnosis. Expert Systems with Applications, 37(2), 1419–1430. 10.1016/j.eswa.2009.06.060

Lu, W., Zhang, Y., Cheng, H., Zhou, Y., & Lv, H. (2020). Research on dynamic behavior of multistage gears-bearings and box coupling system. Measurement, 150, 107096. https://doi.org/10.1016/j.measurement.2019.107096

McNames, J. (2002). Fourier series analysis of epicyclic gearbox vibration. 10.1115/1.1403735

Rai, A., & Upadhyay, S. H. (2016). A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings. Tribology International, 96, 289–306. https://doi.org/10.1016/j.triboint.2015.12.037

Ristić, S. S., Jegdić, B. V., & Polić-Radovanović, S. R. (2013). Investigation of the energy efficiency of the military museum building by infrared thermography. Vojnotehnički Glasnik, 61(2), 182–199. 10.5937/vojtehg61-2901

Shaalan, A. A., Mefteh, W., & Frihida, A. M. (2024). Review on deep learning classifiers for faults diagnosis of rotating industrial machinery. Service Oriented Computing and Applications, 18(4), 361–379. https://doi.org/10.1007/s11761-024-00418-7

Singh, T., & Sehgal, S. (2022). Damage identification using vibration monitoring techniques. Materials Today: Proceedings, 69, 133–141. 10.1016/j.matpr.2022.08.204

Thomas, R., Jones, N., & Donne, K. (2001). Infrared thermography in industrial diagnostics. Measurement and Control, 34(4), 110–112. 10.1177/002029400103400407

Vishwakarma, M., Purohit, R., Harshlata, V., & Rajput, P. (2017). Vibration analysis & condition monitoring for rotating machines: A review. Materials Today: Proceedings, 4(2), 2659–2664. 10.1016/j.matpr.2017.02.140

Watban Khalid Fahmi, A.-T., Reza Kashyzadeh, K., & Ghorbani, S. (2022). A comprehensive review on mechanical failures cause vibration in the gas turbine of combined cycle power plants. Engineering Failure Analysis, 134, 106094. https://doi.org/10.1016/j.engfailanal.2022.106094

Zhang, S. (2013). Green tribology: Fundamentals and future development. Friction, 1(2), 186–194. https://doi.org/10.1007/s40544-013-0012-4

Published
2025/10/14
Section
Original Scientific Papers