Open Access Subscription Access
Numerical and Experimental Study of Vibrations Caused by Defects in Fan Blades
Damage monitoring of rotating blades is becoming increasingly important, because blades in many applications like turbine engines, marine propellers, and turbo engines are exposed to high temperatures, high strains, and severe vibrations. Due to continuous operations of these blades fatigue cracks can emerge after an hour of service, these causes a blade failure and can potentially ruin an entire engine. The damage identification of blades by vibrational analysis is discussed in this paper, numerical analysis is carried out using ANSYS Workbench program to simulate a FEM model, and results are compared to the experimental analysis, where fault simulation machinery equipment used to know the vibration responses of a healthy and defective blades. Multiple distinct peaks were observed at the blade resonance region in case of blades having a defect when compared to healthy blades showing one distinct peak in the blade resonance region which helps in analysis helps in understanding the damage detection of blades early, reducing the likelihood of catastrophic accidents.
Vibration, Damage in fan blades, Mathematical modelling, Blade Health Monitoring.
- Kunpeng Xu , Xianfei Yan, Dalu Xu, Dongxu Du ,Wei Sun, (2021): Detection of blade substrate crack parameters of hard-coated blisk based on mistuning identification technology, Mechanical Systems and Signal Processing 165 10838, Shenyang 110043, China, Elsevier.
- Mengyao Yu , Sheng Fu, Yinbo Gao, Hao Zheng, and Yonggang Xu (2018): Crack Detection of Fan Blade Based on Natural Frequencies, International Journal of Rotating Machinery, Volume Hindawi, Crack Detection of Fan Blade Based on Natural Frequencies (hindawi.com).
- Emilio Di Lorenzo, Giuseppe Petrone, Simone Manzato, Bart Peeters, Wim Desmet and Francesco Marulo, (2016): Damage detection in wind turbine blades by using operational modal analysis, Structural Health Monitoring (2016), Vol. 15(3) 289–301, DOI: 10.1177/ 1475921716642748
- Simon Hoell, Piotr Omenzetter (2021): damage detection in a wind turbine blade based on time series methods, LRF Centre for Safety and Reliability Engineering, Research gate DOI: 10.13140/ 2.1.4816.3843
- Hwanhee Lee, Ji-Seok Song, Seog-Ju Cha and Sungsoo (2013): Dynamic response of coupled shaft torsion and blade bending in rotor blade system, Journal of Mechanical Science and Technology 27 (9) 2585~2597, springer (2013), DOI: 10.1007/s12206-013- 0702-x
- P. Neri, B. Peeters (2015): Non-Harmonic Fourier Analysis for bladed wheels damage detection, Journal of Sound and Vibration 356 (2015) 181–194, Elsevier, http://dx.doi.org/10.1016/j.jsv.2015.06.048
- A. Rama Rao , B.K. Dutta, (2012): Vibration analysis for detecting failure of compressor blade, Engineering Failure Analysis, http://dx.doi.org/10.1016/ j.engfailanal. 2012.05.012
- K. Ravi Prakash Babu, Pothamsetty Kasi V Rao, Md. Abid Ali and B. Raghu Kumar, (2019): Crack Simulations in Shaft-Hub-Blade System using Modal Analysis, ISSN: 2277-3878, Volume-8, Issue-1, International Journal of Recent Technology and Engineering (IJRTE).
- Ding Zhang, Xiaoyan Han, Golam. Newaz , Lawrence D. Favro, and Robert L. Thomas (2011): modelling turbine blade crack detection in sonic ir imaging with a method of creating flat crack surface in fea, Air Force Research Laboratory Materials And Manufacturing Directorate,
- A. K. Batabyal et al. (2008): Crack Detection In Cantilever Beam Using Vibration Response, Vibration Problems ICOVP-2007, Springer.
- Mark Mollineaux, Konstantinos Balafas, Kim Branner, Per Nielsen, Angelo Tesauro, et al. (Jul 2014): Damage Detection Methods on Wind Turbine Blade Testing with Wired and Wireless Accelerometer Sensors. Le Cam, Vincent and Mevel, Laurent and Schoefs, Franck. EWSHM - 7th European Workshop on Structural Health Monitoring, Nantes, France. 2014.
- H. D. Nelson, C. Nataraj (1986): The Dynamics of a Rotor System with a Cracked Shaft, Journal of Vibration, Acoustics, Stress, and Reliability in Design, Vol. 108/189, http://asme.org/terms
- Ming-Chuan Wu and Shyh-Chin Huang, (1998): On the vibration of a cracked rotating blade, Shock and Vibration 5, 317–323. IOS Press
- A. Joshuva and V. Sugumaran, (2019): Crack Detection and Localization on Wind Turbine Blade Using Machine Learning Algorithms: A Data Mining Approach, SDHM, vol.13, no.2, pp.181-203, doi:10.32604/sdhm.2019.00287
- Jun Lin et.al, (2016): Sparse reconstruction of blade tiptiming signals for multi-mode blade vibration monitoring, Mechanical Systems and Signal Processing, http://dx.doi.org/10.1016/ j.ymssp.2016.03.020
- Thomas Krause, Jörn Ostermann, (2020): Damage detection for wind turbine rotor blades using airborne sound, Struct Control Health Monit. 2020; e2520, Wiley publications https://doi.org/10.1002/stc.2520
- Kenneth P. Maynard, Martin Trethewey (2001): Blade and shaft crack detection using torsional vibration measurements : Resampling to improve effective dynamic range, Noise and Vibration Worldwide.
- Xu Jinghui et.al (2021): Crack propagation monitoring of rotor blades using synchroextracting transform, Journal of Sound and Vibration, Elsevier, https:// doi.org/10.1016/j.jsv.2021.116253
- E.A. Ogbonnaya et.al,Analysis of Gas Turbine Blade Vibration Due to Random Excitation, Analysis of Gas Turbine Blade Vibration Due to Random Excitation, http://dx.doi.org/10.5772/58829
- F.L.M. dos Santos, B. Peeters, H. Van der Auweraer, L.C.S. Goes, W. Desmet, (2016): Vibration-based damage detection for a composite helicopter main rotorblade, http://dx.doi.org/10.1016/j.csmssp. 2016.01.001.
Abstract Views: 56
PDF Views: 0