Abstract :
Abstract — Induction motor is critical component in
industrial processes and is frequently integrated in
commercially available equipment. Safety, reliability,
efficiency and performance are the major concerns of
induction motor applications. Due to high reliability
requirements and cost of breakdown, condition monitoring,
diagnosis and Protection increasing importance. Protection
of an induction motor (IM) against possible problems, such
as stator faults, rotor faults and mechanical faults, occurring
in the course of its operation is very important, because it is
very popular in industries. Bearing fault is well known
mechanical fault of IM.41% faults related to bearing in IM.
To avoid break down of IM condition monitoring of motor
bearing condition is very important during the normal
operation. Various classical and AI techniques like fuzzy
logic, neural network, neuro-fuzzy are used for condition
monitoring and diagnosis of IM. Among the above mentioned
AI techniques, Fuzzy logic is the best technique for condition
monitoring and diagnosis of IM bearing condition.
Therefore, the present paper focuses on fuzzy logic
technique. In this paper Fuzzy logic is design for the
condition monitoring and diagnosis of induction motor
bearing condition using motor current and speed. After
applying Fuzzy logic it has been seen that continuous
monitoring of the current and speed values of the motor
conditioned monitoring and diagnosis of induction motor
bearing condition can be done.
