Pengembangan Model Condition-Based Monitoring Multi-Parameter Untuk Deteksi Dini Potensi Kerusakan Pompa Sentrifugal Pada Sistem Distribusi Air Bersih
DOI:
https://doi.org/10.59837/jpnmb.v1i9.336Keywords:
pemantauan berdasarkan kondisi, pompa sentrifugal, sistem distribusi airAbstract
Condition-Based Monitoring (CBM) merupakan metode pemeliharaan prediktif yang mengandalkan pemantauan parameter operasional untuk mendeteksi dini potensi kerusakan. Penelitian ini mengembangkan model CBM multi-parameter untuk memantau kondisi pompa sentrifugal pada sistem distribusi air bersih. Parameter yang diamati mencakup getaran, suhu, dan tekanan, yang dikumpulkan secara berkala dari empat unit pompa. Pengukuran dilakukan menggunakan vibration meter, infrared thermometer, dan manometer. Data dianalisis untuk mendeteksi tren degradasi dan anomali operasional. Hasil penelitian menunjukkan bahwa suhu dan tekanan pada beberapa pompa mengalami fluktuasi, sedangkan nilai getaran tetap berada dalam ambang batas aman. Pompa dengan suhu dan tekanan tidak stabil berpotensi mengalami degradasi performa yang lebih cepat. Penerapan CBM memungkinkan deteksi dini terhadap potensi kegagalan, sehingga dapat mengurangi risiko downtime dan meningkatkan efisiensi pemeliharaan. Studi ini menekankan pentingnya pemantauan berbasis kondisi dalam menjaga keandalan sistem distribusi air bersih, terutama di lingkungan pendidikan yang memiliki keterbatasan anggaran pemeliharaan. Penelitian ini merekomendasikan pemantauan jangka panjang serta analisis lebih lanjut terhadap hubungan antara performa pompa dan konsumsi energi.
References
Ali, A., & Abdelhadi, A. (2022). Condition-Based Monitoring and Maintenance: State of the Art Review. Applied Science, 12. https://doi.org/https://doi.org/10.3390/app12020688
Beebe, R. S. (2004). Predictive Maintenance of Pumps Using Condition Monitoring. Elsevier Ltd.
Bloch, H. P., & Budris, A. R. (2014). Pump User’s Handbook Life Extention (4th ed.). The Fairmont Press, Inc.
Chen, L., Wei, L., Wang, Y., Wang, J., & Li, W. (2022). Monitoring and Predictive Maintenance of Centrifugal Pumps Based on Smart Sensors. Sensors, 22(6). https://doi.org/10.3390/s22062106
Forbes, G. (2011). A review of major centrifugal pump failure modes with application to the water supply and sewerage industries. ICOMS Asset Management Conference Proceedings.
Jardine, A. K. S., Lin, D., & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 20(7), 1483–1510. https://doi.org/10.1016/J.YMSSP.2005.09.012
Kristi-Jo, J. H. G.-R. (2023). Reduce dreaded pump problems or failures with condition monitoring. Www.Plantengineering.Com. https://www.plantengineering.com/articles/reduce-dreaded-pump-problems-or-failures-with-condition-monitoring/
Liu, Y., Huang, Q., Li, H., Li, Y., Li, S., Zhu, R., & Fu, Q. (2024). A Novel Intelligent Condition Monitoring Framework of Essential Service Water Pumps. Applied System Innovation, 7(4). https://doi.org/10.3390/asi7040061
Mobley, R. K. (2002). An introduction to predictive maintenance (Second). Elsevier Science.
Olesen, J. F., & Shaker, H. R. (2020). Predictive maintenance for pump systems and thermal power plants: State-of-the-art review, trends and challenges. Sensors (Switzerland), 20(8). https://doi.org/10.3390/s20082425
Pramono, E., Putra, N. I., Feriadi, I., & Riva’i, M. (2024). Perancangan Pemeliharaan Pompa Air di Kampus POLMAN BABEL Menggunakan Metode Condition-based Monitoring. SNITT, 234–239. https://snitt.polman-babel.ac.id/index.php/snitt/article/view/581
Randall, R. B. (2021). Vibration-based condition monitoring : industrial, automotive and aerospace applications (2nd ed.). John Wiley & Sons Ltd.
Sinha, J. K. (2020). Industrial Approaches in Vibration-Based Condition Monitoring. In Industrial Approaches in Vibration-Based Condition Monitoring. CRC Press. https://doi.org/10.1201/9781315147222
Sunal, C. E., Dyo, V., & Velisavljevic, V. (2022). Review of Machine Learning Based Fault Detection for Centrifugal Pump Induction Motors. IEEE Access, 10(June), 71344–71355. https://doi.org/10.1109/ACCESS.2022.3187718
Teixeira, H. N., Lopes, I., & Braga, A. C. (2020). Condition-based maintenance implementation: a literature review. Procedia Manufacturing, 51(2020), 228–235. https://doi.org/10.1016/j.promfg.2020.10.033
Zhao, W., Egusquiza, M., Valero, C., Valentín, D., Presas, A., & Egusquiza, E. (2020). On the use of artificial neural networks for condition monitoring of pump-turbines with extended operation. Measurement, 163, 107952. https://doi.org/10.1016/J.MEASUREMENT.2020.107952
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