Condition monitoring of squirrel cage induction motors (SCIMs) is indispensible for achieving fault-free working environment. As broken rotor bars (BRBs) are one of the more frequent faults in a SCIM especially where direct-on-line starting is indispensible, as in underground mines, a priori knowledge of fault severity in terms of the number of BRBs assists in effective fault monitoring. In this regard, this paper aims to propose a unique empirical relation to facilitate the determination of number of BRB.
Fast Fourier transform is used to obtain fault sideband amplitudes under varying number of BRBs and load torque for 5.5 kW, 7.5 kW, 10 kW, three-phase, 415 V, 50 Hz SCIMs in MATLAB/Simulink. The nature of variation is decided by an appropriate curve fitting technique for comprehending a unique empirical relation. The proposed empirical relation is validated by bootstrapping and z-test. Furthermore, hardware validation is done using 1 kW laboratory prototype with Labview interface.
The analytical study reveals the dependence of lower and upper sideband amplitudes on the number of BRBs, load torque and machine rating. Therefore, fault severity in terms of number of BRBs is accurately calculated using the proposed empirical relation if load torque, machine rating and amplitudes of lower and upper sidebands are known.
The unique empirical relation proposed in the present work provides accurate knowledge of fault severity in terms of the number of BRBs. This facilitates maintenance scheduling which shall reduce effective downtime and improve production.
