A new fuzzy information optimization processing technique for monitoring the transformer

In the electricity utilities around the world, a large number of power transformers are operating beyond their design life. The reliability and quality of power transformers is vital to system operation. In order to determine the condition of the insulation in transformers, many methods are developed. The most interesting methods for identifying fault conditions of the insulation for oil-filled transformer are dissolved gas analysis (DGA), acoustic analysis for the partial discharge (PD), liquid chromatography, and transfer function techniques. But people only apply single of them to monitoring transformer, and fail to combine the full of information from different methods. This paper establishes a theory prototype of fuzzy information optimization processing technique. It integrates different diagnostic methods and information likes DGA, gas rate, acoustic analysis for the PD, temperatures in transformer, electric current, etc. The method in the paper integrates different theory as to information theory, fuzzy set, expert system. It uses fuzzy mathematics theory to establish the membership function of different information (data) from oil-filled transformer. Other values are got from expert experience directly. Then they are integrated by fuzzy matrix theory. A few numerical examples are given to illustrate the technique which information from different methods.