Research on the machine learning method in fault diagnosis expert systems

被引：0

作者：

Wang, DP ^{[1
]}

Feng, ZS ^{[1
]}

Dong, YY ^{[1
]}

机构：

[1] Hebei Univ Econ & Trade, Dept Comp, Shijiazhuang 050061, Peoples R China

来源：

ISTM/99: 3RD INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT | 1999年

关键词：

machine learning; knowledge acquiring; fault diagnosis;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Machine learning is playing a more and more important role in fault diagnosis expert systems. In this paper, firstly, three kinds of knowledge in diagnosis systems are introduced, namely experience knowledge, causal knowledge and the first law knowledge. Then, we analyze the role of a few existing learning and, on the basis of the above discussion. divide the learning in diagnosis expert systems into three parts, i.e., learning simply learning mutually and learning independently. At last, the frame of fault diagnosis and machine learning is given and the viewpoint that diagnosis and learning are an entity is explained.

引用

页码：371 / 375

页数：5