<![CDATA[Since the 19th century, the use of electric motors continues to grow. Nowadays electric motors have been widely used in various fields of industry. One type of electric motor that is often used is an induction motor. Induction motors work in the presence of induced currents due to the relative difference in rotor rotation with rotating magnetic fields. Induction motors are preferred for industrial purposes because of low cost, easy to maintain, and high efficiency. Induction motors that are used continuously can experience several types of fault. The existence of fault can affect the performance of the induction motor. One of the fault that often occurs in induction motor is the result of stator inter-turn fault. This fault is caused by the gradual deterioration of insulation in the stator winding which cause a short-circuit. Sooner or later, this fault can cause damage to the induction motor in a short time if left unchecked. So, it is very important to monitor the fault in real-time. Therefore, this research proposes a fault estimation method on induction motor. The design of fault estimation based on particle filtering and extended state space equations is used to estimate the stator inter-turn fault. The effectiveness of this approach is validated by use of a computer simulation with using two fault signal represented by η_cc ramp and step signal. The performances of this fault estimation are measured by RMSE and with using 500 particles has smallest RMSE value, which are 0.0112 and 0.0124 for dq current fault when using η_cc ramp signal and 0.2373 and 0.2367 for dq current fault when using η_cc step signal.]]>
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