Correlation Dimension Based the Complex Mechanical Neural Network Diagnosis Model Simulation Research

被引：0

作者：

Zhang, Hao-hua ^{[1
]}

Yu, Xin-he ^{[1
]}

Feng, Wen-jiang ^{[1
]}

Ma, Shi-jun ^{[1
]}

Zhao, Xiao-shu ^{[1
]}

机构：

[1] Shenyang Normal Univ, Coll Phys Sci & Technol, Shenyang, Peoples R China

来源：

2015 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND TECHNOLOGY (ICCST 2015) | 2015年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In view of the complexity and nonlinear characteristics of the mechanical equipment failure, this article combines fractal theory, neural network and expert system together and designs a model of fractal neural network fusion fault diagnosis on the basis of existing model of fault diagnoses and simulations to achieve the real approximation of failure mechanism. This model is used to the simulation and test of plump turbine fault diagnosis. The research shows the model can achieve more precise diagnosis of complex rotating machinery equipment failure.

引用

页码：222 / 226

页数：5

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