Wavelet Transform Based Ball Bearing Fault Detection Scheme for Heavy Duty Mining Electrical Motors under Supply Frequency Regulation using MCSA
Published at : 27 Jan 2018
Volume : IJtech
Vol 9, No 1 (2018)
DOI : https://doi.org/10.14716/ijtech.v9i1.1507
Sinha, A.K., Das, S., Chatterjee, T.K., 2018. Wavelet Transform Based Ball Bearing Fault Detection Scheme for Heavy Duty Mining Electrical Motors under Supply Frequency Regulation using MCSA. International Journal of Technology. Volume 9(1), pp. 170-180
| Ashish Kumar Sinha | Department of Mining Machinery Engineering, Indian Institute of Technology (Indian School of Mines) Dhanbad |
| Sukanta Das | Department of Electrical Engineering, Indian Institute of Technology (Indian School of Mines) Dhanbad |
| Tarun Kumar Chatterjee | Department of Mining Machinery Engineering, Indian Institute of Technology (Indian School of Mines) Dhanbad |
Most heavy duty mining electrical drives employ squirrel cage induction motors (SCIMs) which are subjected to various undesirable stresses. Therefore, condition monitoring of the SCIMs is indispensable for achieving production goals with minimum downtime in a fault-free working environment. Because bearing damage is the most frequently occurring fault in SCIMs, an effective fault detection scheme will aid in achieving production targets in an industrial mining scenario. In this regard, the present work intends to propose an effective fault monitoring algorithm, which is immune to supply frequency regulation, for the detection of ball bearing damage in an SCIM. Discrete Wavelet Transform (DWT) is used for the design of the fault detection scheme. Validation of the proposed scheme is done in a LabVIEW based laboratory interface. The complete analysis is carried out in MATLAB/ Simulink using a 5.5 kW, 3-phase, 415 V, 50 Hz SCIM.
Bearing fault; Condition monitoring; Discrete wavelet transform; Squirrel cage induction motor
The precarious working environment prevalent in mines increases the likelihood of damage to ball bearings. Quick detection is indispensable for reduced downtime of drive systems in underground mines. A DWT-based MRA of stator current for ball bearing damage detection is presented in the present work. The proposed fault detection scheme employs the standard deviation of level-five detailed coefficient [d5] from the pre-fed values of the same for the detection of ball bearing damage, based on the careful choice of an analyzing mother wavelet (‘sym31’ in the present work) and working sampling frequency (6.25 kHz in the present work). The proposed scheme is further validated in real time by a LabVIEW based 5.5 kW SCIM laboratory interface. The proposed scheme is also robust to ± 4% (approx.) supply frequency regulation and ± 1.5% (approx.) sampling frequency variation at a given supply frequency. The implementation of this proposed approach requires a minimal instrumentation system, ideal for the grimy and hazardous mine environment.
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