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Wear loss prediction model of denture material based on radial basis function neural network


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Wear loss prediction model of denture material based on radial basis function neural network
Zheng Kan1Jia Xiuyi2Liao Wenhe1
1.School of Mechanical Engineering;
2.School of Computer Science and Engineering,NUST,Nanjing 210094,China
radial basis function neural network dentures wear loss TC4 alloys ten-fold cross-validation
To research the wear matching of denture materials and teeth,low speed reciprocating wear tests between teeth and TC4 alloys are performed in artificial saliva with different normal loads,sliding frequencies and cycles.Taking 11 groups of test results as training samples,a wear loss prediction model for denture material is proposed based on the radial basis function neural network(RBFNN).The mean absolute error of this model is 0.649 2 by using the 10-fold cross validation method,which verifies the correctness and rationality of the model.Dependency degree of each factor is calculated.The results show that the influences of the tooth normal load,sliding frequency and cycle on the mean absolute error are 0.626 2,0.628 8 and 0.488 6 respectively.


[1] 于世宾,王美青,赵守亮.牙齿磨损的病因学研究进展[J].牙体牙髓牙周病学杂志,2003,13(12):707-710.
Yu Shibin,Wang Meiqing,Zhao Shouliang.Research progression on the etiology of tooth wear[J].Chinese Journal of Conservative Dentistry,2003,13(12):707-710.
[2]Zou Lifong,Cherukara G,Hao Pengwei,et al.Geometrics of tooth wear[J].Wear,2009,266(5/6):605-608.
[3]Pasaribu H R,Reuver K M.Environmental effects on friction and wear of dry sliding zirconia and alumina ceramics doped with copper oxide[J].International Journal of Refractory Metals and Hard Materials,2009,23(4/6):386-390.
[4]Davim J P,Santos E.Comparative study of friction behaviour of alumina and zirconia ceramics against steel under water lubricated conditions[J].Industrial Lubrication and Tribology,2008,60(4):178-182.
[5]Ghazal M,Yang B,Ludwig K,et al.Two-body wear of resin and ceramic denture teeth in comparison to human enamel[J].Dental Materials,2008,24(4):502-507.
[7]Yu J b.Online tool wear prediction in drilling operations using selective artificial neural network ensemble model[J].Neural Computing and Applications,2011,20(4):473-485.
Wang Wenjian,Chen Mingtao,Liu Qiyue.Prediction of wear volumes of rail steel based on BP neural network[J].Lubrication Engineering,2007,32(12):20-22.
Song Jiangteng,Zeng Pan,Zhao Jiaqing,et al.Analysis of stellite alloys wearing prediction based on radial basis function neural network[J].Lubrication Engineering,2011,36(3):30-32,64.
[10]Stober T,Lutz T,Gilde H,et al.Wear of resin denture teeth by two-body contact[J].Dental Materials,2006,22(3):243-249.
[11]Li H,Zhou Z R.Wear behavior of human teeth in dry and artificial saliva conditions[J].Wear,2002,249(10/11):980-984.
Lin Fen,Zhao Youqun.Comparison of methods for estimating vehicle side slip angle[J].Journal of Nanjing University of Science and Technology,2009,33(1):122-126,131.


Last Update: 2013-12-31