Fatigue Life Prediction for Throwing Impeller of an Impeller Blower

doi:10.23940/ijpe.19.01.p13.127137

Abstract

Abstract:

Impeller blowers are used to convey materials for various forage harvesters. As the main working component, the throwing impeller endures various static and dynamic loads while conveying the materials. This makes the throwing impeller prone to fatigue fracture,so it is very necessary to find a feasible model to estimate the fatigue life of the throwing impeller accurately. In order to obtain the accurate random cyclic load applied on the high-speed rotating impeller, the finite element analysis and the fluid-solid coupling method are adopted to calculate the stress distribution of the impeller under the combined action of the fluid-solid coupling flow field pressure, the centrifugal force, and the gravity. At the same time, the stress on the dangerous section of the impeller is measured by using the DH5909 wireless strain testing system and is compared with the calculated one. The contrast results show that the numerical calculation results are reliable. To accurately predict the fatigue life of the throwing impeller at the design stage, the two-parameter nominal stress model is deduced and combined with the linear cumulative damage model of Miner and the lognormal distribution model. Its two parameters of the average stress S_m and the stress amplitude S_a can be obtained through finite element analysis and do not have to be equivalent to a symmetrical cyclic load. Therefore, its precision of estimating the fatigue life is improved. By contrasting the rated and predicted fatigue lives of an impeller, it was found that the impeller’s actual rated lives are closer to the predicted lives of the Goodman and Gerber two-parameter nominal stress model than those of the conventional S-N curve. In particular,they are closer to the calculation results of the Gerber-type two-parameter nominal stress model. This shows that the Gerber-type two-parameter nominal stress model is more accurate and suitable to predict the fatigue life of the throwing impeller. These achievements will play a significant role in further optimizing the impeller and improving its reliability.

Key words: throwing impeller, fatigue life, two-parameter nominal stress model, Miner rule, log-normal distribution

Zhiping Zhai, Can Li, Hongmei Cui, Hongyu Liang, and Haiying Cheng. Fatigue Life Prediction for Throwing Impeller of an Impeller Blower [J]. Int J Performability Eng, 2019, 15(1): 127-137.

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References 19

[1]	Z. P. Zhai, L. Zhou, Z. Y. Yang, Y. Q. Zhao, S. M. Gan , “Analysis on Vibration Characteristics of Throwing Impeller of Stalk Impeller Blower,”Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), Vol. 31, No. 4, pp. 17-25, 2015 ( in Chinese with English abstract)
[2]	Z. P. Zhai, Y. Q. Zhao, H. M. Cui , “Modal Analysis and Structure Optimization for the Throwing Impeller of the Stalk Rubbing Machine,”International Agricultural Engineering Journal, Vol. 25,No. 4, pp. 72-83, 2016
[3]	P. S . Chattopadhyay and P. S. Pandey,“Effect of Knife and Operational Parameters on Energy Requirement in Flail Forage Harvesting,”Agricultural Engineering Research, Vol. 73, No. 2, pp. 3-12, 1999 doi: 10.1006/jaer.1998.0395
[4]	S. Krzysztof and L. Aleksander, “Two-Stage Motion of Particles in the Discharge Spout of Forage Harvester,” Agricultural Engineering,Vol. 124, No. 6, pp. 245-252, 2010
[5]	A. Lisowski, K.Świątek, J. Klonowski , M.Sypuła, J.Chlebowski, “Movement of Chopped Material in the Discharge Spout of Forage Harvester with a Flywheel Chopping Unit: Measurements using Maize and Numerical Simulation,”Biosystems Engineering, Vol. 111, No. 4, pp. 381-391, 2012
[6]	Z. P. Zhai, Z. Y. Yang, B. Gao, J. X. Li , “Simulation of Solid-Gas Two-Phase Flow in an Impeller Blower based on Mixture Model,”Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), Vol. 29, No. 22, pp. 50-58, 2013 ( in Chinese with English abstract) doi: 10.3969/j.issn.1002-6819.2013.22.006
[7]	S. Dileep, S. E. Muthu, P. Udayanan, R. K. Mishra , “Multiaxial Fatigue Damage Prediction and Life Estimation of a Centrifugal Impeller for a Turboshaft Engine,”Journal of Failure Analysis & Prevention, Vol. 16, No. 6, pp. 883-891, 2015 doi: 10.1007/s11668-015-0032-7
[8]	E. M. Shanmugam, R. V. Prakash , S. Ammaiappan, “Probabilistic Fatigue Life Assessment of a Titanium Alloy Impeller for Turbo Shaft Engine Application,”in Proceedings ofASME 2015 Gas Turbine India Conference, 2015
[9]	L. Xu, H. J. Cao, H. L. Liu, Y. B. Zhang , “Assessment of Fatigue Life of Remanufactured Impeller based on FEA,”Frontiers of Mechanical Engineering, No. 3, pp. 219-226, 2016 doi: 10.1007/s11465-016-0394-x
[10]	Q. Liao, H. Z. Huang, S. P. Zhu, D. Ling , “Turbine Disk Fatigue Life Prediction based on Generalized σ-N Surface,”Journal of University of Electronic Science and Technology of China, Vol. 42, No. 2, pp. 316-320, 2013
[11]	D. G. Pavlou , “The Theory of the S-N Fatigue Damage Envelope: Generalization of Linear, Double-Linear, and Non-Linear Fatigue Damage Models,”International Journal of Fatigue,Vol. 110, pp. 204-214, 2018 doi: 10.1016/j.ijfatigue.2018.01.023
[12]	M. Saggar, H.Sallem, C. Bouraoui , “Fatigue Life Prediction under Variable Loading based on a New Damage Model Devoted for Defective Material,”International Journal of Advanced Manufacturing Technology, Vol. 95, No.1- 4, pp. 431-443, 2018 doi: 10.1007/s00170-017-1198-9
[13]	M. L. Aggarwal, V. P. Agrawal, R. A. Khan , “A Stress Approach Model for Predictions of Fatigue Life by Shot Peening of EN45A Spring Steel,”International Journal of Fatigue, Vol. 28, No. 12, pp. 1845-1853, 2006 doi: 10.1016/j.ijfatigue.2005.12.004
[14]	S. Ishihara, A. J. Mcevily, M. Sato, K Taniguchi, T Goshima , “The Effect of Load Ratio on Fatigue Life and Crack Propagation Behavior of an Extruded Magnesium Alloy,”International Journal of Fatigue, Vol. 31, No.11- 12, pp. 1788-1794, 2009 doi: 10.1016/j.ijfatigue.2009.02.034
[15]	S. Z. Zhou, K. Q. Zhu, H. C . Wu, and C. Qiao, “Fatigue Life Analysis of the BlenderTruck Mixing Impeller based on Workbench,”China Petroleum Machinery,No. 2, pp. 36-38, 2012
[16]	J. L. Fan, X. L. Guo, C. W. Wu, and D. W. Deng , “Fast Evaluation of Fatigue Behavior of Q235 Steel by Infrared Thermography and Energy Approach,”Journal of Materials Engineering,Vol. 40,No. 12, pp. 71-76, 2012
[17]	W. X. Liu , “Mechanical Reliability Design, ”Tsinghua University Press, Beijing, 1996
[18]	Z. P. Zhai, L. Zhang, C. Z. Liu, H. N . Li, and H. M. Cui, “Numerical Simulation and Experimental Validation of Radiation Noise from Vibrating Shell of Stalk Impeller Blower,”Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), Vol. 33, No. 16, pp. 72-79, 2017 (in Chinese with English abstract) doi: 10.11975/j.issn.1002-6819.2017.16.010
[19]	J. L. Fan, X. L. Guo, C. W . Wu, and Y. G.Zhao,“Research on Fatigue BehaviorEvaluation and Fatigue Fracture Mechanisms of Cruciform Welded Joints,”Materials Science & Engineering A,Vol. 528, No. 29- 30, pp. 8417-8427, 2011

P(%)	50	90	99
Conventional S-N curve (Gerber)	1.2780×10⁷	7.1867×10⁶	6.2593×10⁶
Conventional S-N curve (Goodman)	7.7963×10⁶	4.3842×10⁶	3.8195×10⁶
Two-parameter model (Goodman)	6.1391×10⁶	3.4522×10⁶	3.0068×10⁶
Two-parameter model (Gerber)	3.2761×10⁶	1.8679×10⁶	1.6046×10⁶
Rating life	3.5×10⁶	2.0×10⁶	1.8×10⁶