Abstract
Structure frequency response testing “modal analysis” is an integral part of the development and testing of structures such as pistons, turbine blades, compressor blades, crankshafts, and connecting rods. The usefulness of this technique lies in the fact that the energy in an impulse input is distributed continuously in the frequency domain. Thus, an impulse force will excite all resonances within given frequency range. To detect a fault in the structure, one may require frequency response functions (FRFs) of structures in both conditions, before (healthy structure) and after (failed structure) fault occurs. Now by extracting modal properties from collected FRFs and by comparing modal properties, one can detect and locate the structural faults. A case study is presented in order to detect failure mode and locate cracks on a 30 MW first stage gas turbine blade made of nickel based super alloy IN738LC, which has failed after rendering a useful life of 72000 h. The root causes of failure are detected by comparing the failed blade experimental model with the failed blade computational model. It is observed that the frequencies of the real failed blade experimental model are lesser than the computational model of the failed turbine blade. This is due to the metallurgical defects, which result in loosening of stiffness at the leading and trailing edges of the blade. Further, the stress concentration areas noticed on leading and trailing edges in computational model of the failed blade at the sixth mode are well corroborated with the cracked zone seen on leading and trailing edges of a real case failed turbine blade, collected from the site. It is concluded that the blade has failed due to that the resonance at sixth modal frequency. Scanning electron microscope (SEM) images reveal the presence of corrosion pits on the surfaces of the turbine blade that lead to surface degradation, which results in crack initiation and its propagation with high-cycle fatigue. It is concluded that the failure of turbine blade occurs due to high cycle fatigue.
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S. Rani has her Ph.D. in Machine Design (Vibrations) from Delhi Technological University, Delhi, India. Presently, she is working as Assistant Professor in Mechanical, Production, Industrial and Automobile Engineering Department at Delhi Technological University, Delhi, India. Her research interest is fault diagnosis in Machinery.
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Rani, S., Agrawal, A.K. & Rastogi, V. Vibration analysis for detecting failure mode and crack location in first stage gas turbine blade. J Mech Sci Technol 33, 1–10 (2019). https://doi.org/10.1007/s12206-018-1201-x
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DOI: https://doi.org/10.1007/s12206-018-1201-x