Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
381638 | Engineering Applications of Artificial Intelligence | 2006 | 11 Pages |
Abstract
This is the second part of our study on condition monitoring using fuzzy transition probability (FTP). In the first paper, the theory of FTP is presented. In this paper, in order to validate the theory, two practical examples are given. The first one is a material tensile strength test and the second one was tool condition monitoring in boring. The experiment results indicate that the new method is effective. It outperforms the popular artificial neural network method (feed-forward network with back propagation training) by as much as 9%.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
R. Du, K. Yeung,