Abstract
In order to obtain friction and wear performance of different brakes in different conditions with less test data, back propagation artificial neural network model has been established by some physical parameters and working conditions to train and predict friction and wear performance of carbon brake disk. The predicted values for training and investigating are accuracy in comparison with the real test data, and factors to influence brake performance have been quantitatively analyzed by principal component analysis. The result shows that heat-sinking capability and working condition might be the primary cause for brake friction and wear difference, and the methods above could be applied to friction and wear performance prediction and factor analysis in engineering practice.
Similar content being viewed by others
References
Akhtar MN, Nasir N, Kashif M, Yahya N, Ahmade M, Murtaza G (2014) Mn0.8Zn0.2Fe2O4 nanoparticulates spinel ferrites: an approach to enhance the antenna field strength for improved magnitude versus offset (MVO). Progress Nat Sci Mater Int 24:364–372. https://doi.org/10.1016/j.pnsc.2014.06.005
Aleksendrić D (2010) Neural network prediction of brake friction materials wear. Wear 268:117–125
Aleksendrić D, Barton DC (2009) Neural network prediction of disc brake performance. Tribol Int 42:1074–1080
Aleksendrić D, Barton DC, Vasić B (2010) Prediction of brake friction materials recovery performance using artificial neural networks. Tribol Int 43:2092–2099
Deng HL, Li KZ, Li HJ, Wang PY, Xie J, Zhang LL (2010) Effect of brake pressure and brake speed on the tribological properties of carbon/carbon composites with different pyrocarbon textures. Wear 270(1):95–103
Feng L, Zhong W, Jian-Lin G, Li-Zhen S, Qing Y (2008) Dynamic changes of mineral element in the cell wall of growth cells detected by CSEM-EDX. Progress Biochem Biophys 35(2):170–179. Available online at www.pibb.ac.cn
Frank HFL (2003) Tuning of the structure and parameters of a neural network using an improved genetic algorithm. IEEE Trans Neural Netw 14:10–13
Ghosh S (2002) Electricity consumption and economic growth in India. Energy Policy 30:125–129
Li JH (2004) “Friction and wear behavior of C/C composite for aircraft brakes,” master’s degree thesis, Central South University, Changsha, CHN. http://d.g.wanfangdata.com.cn/Thesis_W007650.aspx (in Chinese)
Li JH, Xiong X, Huang BY (2004) Effect of braking speed on friction and wear behaviors of C/C composites. Mater Protect 37(7):75–76 (in Chinese)
Li JH, Xiong X, Zhang HB, Yu S, Xiao P, Huang BY (2007) Study of friction properties and friction surface of carbon/carbon composites at different braking pressure. Lubricat Eng 32(4):9–13 (in Chinese)
Luo W, Xiong W, Qiu M, Lv Y, Li Y, Li F (2011) Differentiation of mesenchymal stem cells towards a nucleus pulposus-like phenotype utilizing simulated microgravity in vitro. J Huazhong Univ Sci Technol [Med Sci] 31(2):199–203. https://doi.org/10.1007/s11596-011-0252-3
Roudgarmi P, Monavari M, Feghhi J, Nouri J, Khorasani N (2008) Environmental impact prediction using remote sensing images. J Zhejiang Univ Sci A 9(3):381–390. https://doi.org/10.1631/jzus.A072222
Senatore A, D’Agostino V, Di Giuda R, Petrone V (2011) Experimental investigation and neural network prediction of brakes and clutch material frictional behaviour considering the sliding acceleration influence. Tribol Int 44:1191–1207
Senthilkumar K, Srinivasan PSS (2010) Application of Taguchi method for the optimization of system parameters of centrifugal evaporative air cooler. J Therm Sci 19(5):473–479. https://doi.org/10.1007/s11630-010-0411-z
Shorowordi KM, Haseeb ASMA, Celis JP (2004) Velocity effects on the wear, friction and tribochemistry of aluminum MMC sliding against phenolic brake pad. Wear 256(11):1176–1181. https://doi.org/10.1016/j.wear.2003.08.002
Singh KP, Malik A, Sinha S et al (2005) Estimation of source of heavy metal contamination in sediments of Gomtiriver (India) using principal component analysis. Water Air Soil Pollut 166:321–341
Su JM, Xiao ZC, Liu YQ, Meng FC, Peng ZG, Gu LM, Li GF, Xing RP (2010) Preparation and characterization of carbon/carbon aircraft brake materials with long service life and good frictional properties. N Carbon Mater 25(5):329–334. https://doi.org/10.1016/S1872-5805(09)60037-8
Su JM, Ji GM, Li GF, Zhang T, Zhu ZQ, Xiao ZC (2011) Research on service life of the aircraft carbon brake disks. Carbon 4:7–11. https://doi.org/10.3969/j.issn1001-8948.2011.04-002 (in Chinese)
Tian Y, Liu H, Yin J, Luo M, Wu G (2015) Evaluation of simulation-based training for aircraft carrier marshalling with learning cubic and Kirkpatrick’s models. Chin J Aeronaut 28(1):152–163. https://doi.org/10.1016/j.cja.2014.12.002
Wen SZ, Huang P (2008) Principle of tribology. Tsinghua University Press, Beijing, pp 306–307 (in Chinese). ISBN 978-7-302-17946-7
Xiong X, Zhang HB, Li JH (2004) Friction and wear properties of carbon/carbon composites under different braking pressure. J Cent South Univ (Science and Technology) 35(5):720–724 (in Chinese)
Xiong X, Huang BY, Li JH, Xu HJ (2006) Friction behaviors of carbon/carbon composites with different pyrolytic carbon textures. Carbon 44(3):463–467
Xiong X, Li JH, Huang BY (2007) Impact of brake pressure on the friction and wear of carbon/carbon composites. Carbon 45(13):2692–2694. https://doi.org/10.1016/j.carbon.2007.08.029
Zeng Y, Wang L, Du J, Liu J, Yang S, Pu X, Xiao F (2009) Elemental content in brown rice by inductively coupled plasma atomic emission spectroscopy reveals the evolution of asian cultivated rice. J Integr Plant Biol 51(5):466–475. Available online at www.jipb.net
Zhang L, Xiang Z, Luo H, Tian G (2015) Test verification and design of the bicycle frame parameters. Chin J Mech Eng 28(4):716–725. https://doi.org/10.3901/CJME.2015.0505.068
Zhenyuan J, Jianwei M, Fuji W, Wei L (2010) Characteristics prediction method of electro-hydraulic servo valve based on rough set and adaptive neuro-fuzzy inference system. Chin J Mech Eng 23(2):200–208. https://doi.org/10.3901/CJME.2010.02.200
Zhou B, Lin SL, Chang F, Shi XP, Yin JJ (2015) Calculation of brake disk life based on unsteady discontinuous brake. J Beijing Univ Aeronaut Astronaut 41(3):538–544
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhou, B., Li, S. Prediction and Factor Analysis for Friction and Wear Performance of Brake Disk. Iran J Sci Technol Trans Mech Eng 43, 245–252 (2019). https://doi.org/10.1007/s40997-017-0124-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40997-017-0124-y