An Experimental Study on Condition Monitoring and Fault Diagnosis of a Cooling Water Pump using Vibration Analysis

پذیرفته شده برای ارائه شفاهی ، صفحه 1-8 (8)

کد مقاله : 1019-ISAV2023 (R1)

نویسندگان

Ahmad Mahdian Parrany ¹ ، Danial Dayyani ¹ ، Morteza Abbasinejad ¹ ، Hossein Mohammadi Far ²

¹Condition Monitoring Unit, Smelting Department, Sarcheshmeh Copper Complex, Rafsanjan, Iran.

²Operation and Repair Unit of Water and Compressed Air Optimization, Smelting Department, Sarcheshmeh Copper Complex, Rafsanjan, Iran.

چکیده

Nowadays condition monitoring and fault diagnosis based on the vibration data is one of the most common approaches in minimizing the maintenance and repair costs of industrial machines. The current paper represents the results of the condition monitoring and fault diagnosis of a cooling water pump using the vibration analysis. In this regard, the machine under study is described, and its operating condition is investigated based on the existing charts and standards. The measured vibration signals, i.e. velocity in the low frequency range and acceleration in the high frequency range, are quantified and analyzed to find the defective component of the machine, while the frequency analysis is utilized to detect the type of the fault. The vibration signals and the frequency analysis predict some faults in the inner race and rolling elements of one of the bearings of the machine. Finally, some experimental observations are reported to validate the results obtained from the vibration analysis.

کلیدواژه ها

Condition Monitoring؛ Fault diagnosis؛ Vibration Analysis؛ Bearing Fault Detection

موضوعات

Condition Monitoring؛ Condition monitoring - damage detection

Title

An Experimental Study on Condition Monitoring and Fault Diagnosis of a Cooling Water Pump using Vibration Analysis

Authors

Abstract

Keywords

Condition Monitoring, Fault diagnosis, Vibration Analysis, Bearing Fault Detection

مراجع

1. A.R. Mohanty, Machinery Condition Monitoring: Principles and Practices, Taylor & Francis Group: CRC Press, 2015.
2. C. Mongia, D. Goyal, S. Sehgal, “Vibration response–based condition monitoring and fault diagnosis of rotary machinery”, Materials Today: Proceedings 50, 679–683 (2022).
3. C. Malla, I. Panigrahi, “Review of Condition Monitoring of Rolling Element Bearing Using Vibration Analysis and Other Techniques”, Journal of Vibration Engineering & Technologies 7, 407–414 (2019).
4. A. Choudhary, D. Goyal, S.L. Shimi, A. Akula, “Condition monitoring and fault diagnosis of induction motors: A review”, Archives of Computational Methods in Engineering 26, 1221–1238 (2019).
5. J.C.A.J. Correa, A.A.L. Guzman, Mechanical Vibrations and Condition Monitoring, Academic Press, 2020.
6. S.K. Gundewar, P.V. Kane, “Condition monitoring and fault diagnosis of induction motor”, Journal of Vibration Engineering & Technologies 9, 643–674 (2021).
7. Z. Liu, L. Zhang, "A review of failure modes, condition monitoring and fault diagnosis methods for large–scale wind turbine bearings", Measurement 149, 1–22 (2020).
8. S. Kim, D. An, J.H. Choi, “Diagnostics 101: A Tutorial for fault diagnostics of rolling element bearing using envelope analysis in MATLAB”, Applied Sciences 10, 1–23 (2020).
9. I. Aydın, M. Karaköse, E. Akın, “Combined intelligent methods based on wireless sensor networks for condition monitoring and fault diagnosis”, Journal of Intelligent Manufacturing 26, 717–729 (2015).
10. J. Zarei, M.A. Tajeddini, H.R. Karimi, “Vibration analysis for bearing fault detection and classification using an intelligent filter”, Mechatronics 24, 151–157 (2014).
11. F. Jiang, Z. Zhu, W. Li, G. Chen, G. Zhou, “Robust condition monitoring and fault diagnosis of rolling element bearings using improved EEMD and statistical features”, Measurement Science and Technology 25, 1–14 (2014).
12. Y. Lei, N. Li, J. Lin, Z. He, “Two new features for condition monitoring and fault diagnosis of planetary gearboxes”, Journal of Vibration and Control 21, 755–764 (2015).
13. S. Lu, P. Zhou, X. Wang, Y. Liu, F. Liu, J. Zhao, “Condition monitoring and fault diagnosis of motor bearings using undersampled vibration signals from a wireless sensor network”, Journal of Sound and Vibration 414, 81–96 (2018).
14. N.W. Nirwan, H.B. Ramani, “Condition monitoring and fault detection in roller bearing used in rolling mill by acoustic emission and vibration analysis”, Materials Today: Proceedings 51, 344–354 (2022).
15. C. Nicholls, Preventive Maintenance using Vibration Analysis, IRD Mechanalysis Inc., 1970.
16. T.A. Harris, Rolling Bearing Analysis, John Wiley & Sons, Inc., 2001.