An Expert System for Transformer Fault Diagnosis Using Dissolved Gas 

Analysis 

1. INTRODUCTION 

The power transformer is a major apparatus in a power system, and its correct 

functioning 

its 

vital 

to 

minimize 

system 

outages, 

many 

devices 

have 

evolved 

to 

monitor 

the 

serviceability 

of 

power 

transformers. 

These 

devices, 

such 

as, 

Buchholz 

relays 

or 

differential 

relays, 

respond 

only 

to 

a 

severe 

power 

failure 

requiring 

immediate 

removal 

of 

the 

transformer 

from 

service, 

in 

which 

case, 

outages 

are 

inevitable. 

Thus, 

preventive 

techniques 

for 

early 

detection 

faults 

to 

avoid 

outages 

would be valuable. In this way, analysis of the mixture of the faulty gases dissolved in 

insulation oil of power transformer has received worldwide recognition as an effective 

method for the detection of oncipient faults. Many researchers and electrical utilities 

have reported on their experience and developed interpretative criteria on the basis of 

DGA. 

However, 

criteria 

tend 

to 

vary 

from 

utility 

to 

utility. 

Therefore, 

transformer 

diagnosis is still in the heuristic stage. For this reason, knowledge-based programming 

is a suitable approach to implement in such a diagnostic problem. 

Based on the interpretation of DGA, a prototype of an expert system for diagnosis of 

suspected 

transformer 

faults 

and 

their 

maintenance 

procedures 

is 

proposed. 

The 

significant source in this knowledge base is the gas ratio method. Some limitations of 

this 

approach 

are 

overcome 

by 

incorporating 

the 

diagnostic 

procedure 

and 

the 

synthetic expertise method. Furthermore, data bases adopted from TPC'S gas records 

of 

transformers 

are 

incorporated 

into 

the 

expert 

system 

to 

increase 

the 

practical 

performance. Uncertainty of diagnosis is managed by using fuzzy set concepts. This 

expert system is constructed with rule based knowledge representation, since it can be 

expressed 

by 

experts. 

The 

expert 

system 

building 

tool,knowledge 

Engineering 

System(KES), 

is 

used 

in 

the 

development 

of 

the 

knowledge 

system 

because, 

it 

has 

excellent 

man-machine 

interface 

that 

provides 

suggestions. 

Moreover,its 

inference 

strategy is similar to the MYCIN. A famous rule-based expert system used for medical 

diagnosis. 

The 

uncertainty 

of 

human 

qualitative 

diagnostic 

expertise, 

e.g., 

key 

gas