scholarly journals The hybrid uncertain neural network method for mechanical reliability analysis

2015 ◽  
Vol 16 (4) ◽  
pp. 510-519 ◽  
Author(s):  
Wensheng Peng ◽  
Jianguo Zhang ◽  
Lingfei You
2013 ◽  
Vol 838-841 ◽  
pp. 250-253
Author(s):  
Li Rong Sha ◽  
Yue Yang

The artificial neural network is used to solve the reliability analysis of the engineering structure. When the limit state function of structure is highly complex or with nonlinearity, it is time-consuming or cumbersome to carry out reliability analysis with traditional methods. The artificial neural network response surface method is adopted to analyze the fatigue reliability of loader boom, the working process of loader machine is analyzed with FEM software and analytical method, the stress-time history and strain-time history of loader boom are schematized with rain-flow algorithm, consequently the fatigue life analysis on the structure can be carried out with local stress-strain method. The artificial neural network method is used to fit the performance function as well as its derivatives, so as to calculate the reliability of the structure. The numerical example results show that the proposed method has capability of solving industrial-scale reliability problems.


Methods for evaluation the manufacturability of a vehicle in the field of production and operation based on an energy indicator, expert estimates and usage of a neural network are stated. By using the neural network method the manufacturability of a car in a complex and for individual units is considered. The preparation of the initial data at usage a neural network for predicting the manufacturability of a vehicle is shown; the training algorithm and the architecture for calculating the manufacturability of the main units are given. According to the calculation results, comparative data on the manufacturability vehicles of various brands are given.


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