Articles | Open Access |

CHECKING THE RELIABILITY OF PUMP UNITS BASED ON VIBRODIAGNOSTIC INDICATORS

Adilov Ozodbek Komiljon o'g'li , Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Ph.D student,

Abstract

This paper explores the principles of vibrodiagnostics, focusing on how vibration indicators like amplitude, frequency, and phase can reveal common pump problems such as unbalance, misalignment, cavitation, bearing wear, and loose parts. The use of spectrum analysis and time domain analysis for diagnosing specific faults is discussed. The article highlights how vibrodiagnostics enables proactive maintenance strategies, reducing downtime, improving efficiency, and minimizing maintenance costs. Case studies and examples showcase the practical applications of vibrodiagnostics in ensuring pump reliability and promoting safe operations. By adopting vibrodiagnostic programs, industries can significantly enhance the performance and longevity of their pump units, leading to improved overall productivity and profitability.

Keywords

vibrodiagnostics, reliability of pump, vibration signals

References

Predictive Maintenance of Centrifugal Pumps Using Vibration Analysis: A Case Study. Journal of Vibration and Control, Vol. 21, No. 13, pp. 2594-2607, 2015.

Fault Diagnosis of Centrifugal Pumps Based on Vibration Signals: A Review. Sensors, Vol. 19, No. 14, p. 3121, 2019

Vibroacoustic Diagnostics for Condition Monitoring of Rotating Machinery. Mechanical Systems and Signal Processing, Vol. 13, No. 2, pp. 181-202, 1999.

A Review of Vibration-Based Condition Monitoring Techniques for Rotating Machinery. Journal of Sound and Vibration, Vol. 264, No. 3, pp. 595-620, 2003

Predictive Maintenance of Industrial Machinery: A Review. Reliability Engineering & System Safety, Vol. 112, pp. 1-24, 2012.

Pump Reliability: A Guide to Improving Performance and Reducing Costs. Pump Industry Association (PIA), 2019.

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CHECKING THE RELIABILITY OF PUMP UNITS BASED ON VIBRODIAGNOSTIC INDICATORS. (2024). International Journal of Artificial Intelligence, 4(07), 150-153. https://www.academicpublishers.org/journals/index.php/ijai/article/view/1229