Developing Tool Identification System Using Fanuc C Executor

In this paper, a new method of tool condition monitoring in milling by fuzzy set theory has been studied,the relationship between the tool conditions and monitoring indices (features ) is described by a linear fuzzy equation, theparameters of this equation are determined in accordance with the possibility and the probability distributions of thelearning samples.

Application of rough sets theory in flame image processing and state recognition;

Equipment degradation state recognition and fault prognosis method based on wavelet correlation feature scale entropy and HSMM;

Research on equipment degradation state recognition and fault prognostics method based on KPCA-Hidden Semi-Markov Model

Research on Cutting Status Recognition Based on Wavelet packets and Hidden Markov Model;

Human status recognition method for the life detection radarbased on the harmonic model;

For milling-cutter-status recognition,in order to well fit training sample data,the algorithm of integrating linear machine and rough set is applied.

Equipment condition recognition with multi-category support vector machine in wireless sensor networks;

Machine condition recognition based on kernel principal component analysis;

The research for tribology by system method and the condition recognition for the tribology system;