NEW INTUITIONISTIC FUZZY DIVERGENCE MEASURE AND ITS APPLICATIONS TO HANDLE FAULT DIAGNOSIS OF TURBINE

Abstract

The literature of probability, fuzzy and intuitionistic fuzzy divergence measures provides the applications of a variety of divergence measures to different disciplines dealing with real life problems.  Many such divergence measures have been generated through different approaches but still there is a scope that better ones can be developed which will provide applications to variety of disciplines.  The present communication involving the development of a new intuitionistic measure of divergence for fuzzy distributions is a motivation in this direction.  The newly proposed mathematical model is helpful for the study of fault diagnosis of turbine.  In the present paper, we have provided an algorithm which can handle the main faults in the turbine along with useful information for future trends and verified the results numerically.