Reliability Analysis of Automobile Engine Connecting Rod Using Fourier Orthogonal Neural Network Method

• Published in: Applied Mechanics and Materials Vol. 635-637; pp. 430 - 433
• Main Authors: Wang, Tong Yu, Sha, Li Rong
• Format: Journal Article
• Language: English
• Published: Zurich Trans Tech Publications Ltd 01.09.2014
• Subjects: Connecting Rod; Orthogonal Function; Reliability; Artificial Neural Network (ANN)
• ISBN: 3038352578; 9783038352570
• ISSN: 1660-9336; 1662-7482; 1662-7482
• DOI: 10.4028/www.scientific.net/AMM.635-637.430

In order to predict the failure probability of a complicated structure, the structural responses usually need to be estimated by a numerical procedure, such as finite element method (FEM). To reduce the computational effort required for reliability analysis, response surface method could be used. However the conventional response surface method is still time consuming especially when the number of random variables is large. In this paper, a Fourier orthogonal neural network (FONN)-based response surface method is adopted to solve the reliability analysis of the automobile engine. The working process of the connecting rod is simulated with UG software, the dynamics analysis on crank-connecting rod-piston mechanism is performed with ANSYS and ADAMS software, with FEM analysis results, the stress information of the critical point of the structure can be obtained, so the performance function of the structure can be established. The FONN method is used to fit the performance function as well as its derivatives, so as to calculate the reliability of the structure.