Research Papers

PowerGen Gas Turbine Losses and Condition Monitoring: A Loss Data-Based Study

[+] Author and Article Information
Bin Zhou

Risk, Reliability and Failure Prevention Area, FM Global Research,
1151 Boston-Providence Turnpike, Norwood, MA 02062
e-mail: bin.zhou@fmglobal.com

Manuscript received February 23, 2015; final manuscript received October 29, 2015; published online January 4, 2016. Assoc. Editor: Chimba Mkandawire.

ASME J. Risk Uncertainty Part B 2(2), 021007 (Jan 04, 2016) (6 pages) Paper No: RISK-15-1024; doi: 10.1115/1.4031915 History: Received February 23, 2015; Accepted October 29, 2015

In situ condition monitoring (CM) is a crucial element in protection and predictive maintenance of large rotating PowerGen equipment, such as gas turbines or steam turbines. In this work, selected gas turbine loss events occurring during a recent 10-year period at our clients’ power generation plants were evaluated. For each loss event, a loss scenario or a chain of failures was outlined after investigating the available loss record. These loss events were then categorized based on the nature of the associated loss scenario. The study subsequently focused on the variables that could be monitored in real-time to detect the abnormal turbine operating conditions, such as vibration characteristics, temperature, pressure, quality of working fluids, and material degradations. These groups of CM variables were then matched with detectable failures in each loss event and prioritized based on their effectiveness for failure detection and prevention. The detectable loss events and the associated loss values were used in this evaluation process. The study finally concluded with a summary of findings and path-forward actions.

Copyright © 2016 by ASME
Your Session has timed out. Please sign back in to continue.


Simmons, H. R., Brun, K., and Cheruvu, S., 2006, “Aerodynamic Instability Effects on Compressor Blade Failure: A Root Cause Failure Analysis,” Proceedings of ASME Turbo Expo, ASME, New York, Vol. 5, pp. 649–660. 10.1115/GT2006-91353
Latcovich, J. A., 2002, “Condition Monitoring and Its Effect on the Insurance of New Advanced Gas Turbines,” Turbine Power Systems Conference and Condition Monitoring Workshop, Galveston, TX, NETL-DOE, Houston, TX, pp. 25–27.
Roorda, B., 2009, “Prognostic Health Management (PHM) System for Monitoring Blade Vibrations in Turbo Machinery,” Presented at the Propulsion—Safety and Affordable Readiness Forum, Myrtle Beach, SC.
Zielinski, M., and Ziller, G., 2005, “Noncontact Crack Detection on Compressor Rotor Blades to Prevent Further Damage after HCF-Failure,” NATO, RTO (Research and Technology Organization)-MP (Meeting Proceedings)-AVT-121, Applied Vehicle Technology Panel Symposium, Granada, Spain, NATO STO – CSO, Neuilly-sur-Seine, France.
Sheng, S., 2011, “Investigation of Oil Conditioning, Real-Time Monitoring and Oil Sample Analysis for Wind Turbine Gearboxes,” Presented at the AWEA (American Wind Energy Association) Project Performance and Reliability Workshop, San Diego, CA.
Sheiretov, Y., Grundy, D., Zilberstein, V., Goldfine, N., and Maley, S., 2009, “MWM-Array Sensors for In Situ Monitoring of High-Temperature Components in Power Plants,” Sens. J., 9(11), pp. 1527–1536. 10.1109/JSEN.2009.2019335
Momeni, S., Koduru, J. P., Gonzalez, M., and Godinez, V., 2013, “Online Acoustic Emission Monitoring of Combustion Turbines for Compressor Stator Vane Crack Detection,” Proceedings of SPIE, Industrial and Commercial Applications of Smart Structures Technologies, SPIE, Bellingham, WA, Vol. 8690, pp. 86900B. 10.1117/12.2013870


Grahic Jump Location
Fig. 1

Percentages of total loss value and loss count by loss categories

Grahic Jump Location
Fig. 2

Normalized average loss value by loss categories

Grahic Jump Location
Fig. 3

Compressor versus turbine losses

Grahic Jump Location
Fig. 4

Blade vibrations: cause and effect

Grahic Jump Location
Fig. 5

Blade failure scenario and monitoring variables

Grahic Jump Location
Fig. 6

Percentages of total loss value and loss counts detectable by groups of CM variables

Grahic Jump Location
Fig. 7

Blade and rotor vibration monitoring




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Articles from Part A: Civil Engineering
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In