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Blade Faults Diagnosis in Power Generation Gas Turbines

[+] Author Affiliations
Meng Hee Lim, Salman Leong, Kar Hoou Hui

Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

Paper No. POWER-ICOPE2017-3716, pp. V002T08A021; 5 pages
doi:10.1115/POWER-ICOPE2017-3716
From:
  • ASME 2017 Power Conference Joint With ICOPE-17 collocated with the ASME 2017 11th International Conference on Energy Sustainability, the ASME 2017 15th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2017 Nuclear Forum
  • Volume 2: I&C, Digital Controls, and Influence of Human Factors; Plant Construction Issues and Supply Chain Management; Plant Operations, Maintenance, Aging Management, Reliability and Performance; Renewable Energy Systems: Solar, Wind, Hydro and Geothermal; Risk Management, Safety and Cyber Security; Steam Turbine-Generators, Electric Generators, Transformers, Switchgear, and Electric BOP and Auxiliaries; Student Competition; Thermal Hydraulics and Computational Fluid Dynamics
  • Charlotte, North Carolina, USA, June 26–30, 2017
  • Conference Sponsors: Power Division, Advanced Energy Systems Division, Solar Energy Division, Nuclear Engineering Division
  • ISBN: 978-0-7918-5761-8
  • Copyright © 2017 by ASME

abstract

This paper presents a case study in managing the dilemma of whether to resume or stop the operation of a power generation gas turbine with suspected blade faults. Vibration analysis is undertaken on the vibration signal of the gas turbine, to obtain an insight into the health condition of the blades before any decision is made on the operation of the machine. Statistical analysis is applied to study the characteristics of the highly unstable blade pass frequency (BPF) of the gas turbine and to establish the baseline data used for blade fault assessment and diagnosis. Based on the excessive increase observed on specific BPF amplitudes in comparison to the statistical baseline data, rubbing at the compressor blade is suspected. An immediate overhaul is therefore warranted, and the results from the inspection of the machine confirm the occurrence of severe rubbing at the compressor blades and labyrinth glands of the gas turbine. In conclusion, statistical analysis of BPF amplitude is found to be a viable tool for blade fault diagnosis in industrial gas turbines.

Copyright © 2017 by ASME

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