scholarly journals Intelligent Condition Monitoring Techniques for Early Fault Diagnosis of Rotating Machines – A Review

2021 ◽  
Vol 23 (08) ◽  
pp. 549-566
Author(s):  
Vinod Kumar ◽  
◽  
S.S Dhami ◽  
Deepam Goyal ◽  
◽  
...  

Condition-based maintenance is always an important strategy of maintenance to prolong the effective life of rotating machines as they run on high speeds with a variety of loads in some cases under severe conditions. If the monitoring of the current condition is not done accurately then rotating machines such as turbines, engine, bearing, shafts, gearbox, motors, and compressors leads to catastrophic failures with some serious consequences on the rate of production, safety, loss of manpower and sudden increase in repairing cost. Condition-based maintenance is also be called predictive type maintenance is a far superior technique as compared to preventive maintenance and run-to-break maintenance. In predictive maintenance current status of the machine while in operation, being monitored carefully and based on a brief analysis of the future condition of the machine predicted. This paper going to review the various intelligent condition monitoring techniques developed or used by various researchers to monitor the health of rotating machines and able to predict the faults at the earliest time.

2014 ◽  
Vol 6 ◽  
pp. 210717 ◽  
Author(s):  
Ahmed M. Abdelrhman ◽  
Lim Meng Hee ◽  
M. S. Leong ◽  
Salah Al-Obaidi

Blade faults and blade failures are ranked among the most frequent causes of failures in turbomachinery. This paper provides a review on the condition monitoring techniques and the most suitable signal analysis methods to detect and diagnose the health condition of blades in turbomachinery. In this paper, blade faults are categorised into five types in accordance with their nature and characteristics, namely, blade rubbing, blade fatigue failure, blade deformations (twisting, creeping, corrosion, and erosion), blade fouling, and loose blade. Reviews on characteristics and the specific diagnostic methods to detect each type of blade faults are also presented. This paper also aims to provide a reference in selecting the most suitable approaches to monitor the health condition of blades in turbomachinery.


1998 ◽  
Author(s):  
J. Pearson ◽  
B.F. Hampton ◽  
M.D. Judd ◽  
B. Pryor ◽  
P.F. Coventry

2021 ◽  
pp. 29-39
Author(s):  
Rubia Ramesh Kumar ◽  
Saloni Sharma ◽  
Priyank Mehra ◽  
V. Berlin Hency ◽  
O.V. Gnana Swathika

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