Induction Motor Test Rig

Figure 1 Induction test rig

Test rig description

The induction motor test rig (Figure 1) mainly includes an induction motor (rated power 4kW) and a DC generator which is mechanically coupled with the motor to provide various loads. A PLC is used to control the speed and load to simulate different operating conditions.

Instrumentation

The signals measured from the test rig include, three phase voltage and current, one encoder signal on the motor drive end and two vibration signals on the motor casing, one temperature sensor on the motor casing. All signals are acquired with a 24-bit, 16-channel, synchronous Data Acquisition (DAQ) system at a sampling frequency of 96 kHz.

Typical fault simulation

The test rig can simulate several typical faults, including rotor fault, stator fault, bearing fault, axle fault and combined faults, as shown in Table 1. Furthermore, different operating conditions can be controlled with speed ranging from 0 rpm to 1420 rpm and load ranging from 0% to 100%.

Table 1 Typical fault simulation

Key publications
  • [1] Gu, F., Wang, T., Alwodai, A., Tian, X., Shao, Y. and Ball, A.D., 2015. A new method of accurate broken rotor bar diagnosis based on modulation signal bispectrum analysis of motor current signals. Mechanical Systems and Signal Processing, 50, pp.400-413.
  • [2] Li, H., Feng, G., Zhen, D., Gu, F. and Ball, A.D., 2020. A Normalized Frequency Domain Energy Operator for Broken Rotor Bar Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement.
  • [3] Lane, M., Ashari, D., Gu, F. and Ball, A.D., 2015. Investigation of motor current signature analysis in detecting unbalanced motor windings of an induction motor with sensorless vector control drive. In Vibration Engineering and Technology of Machinery (pp. 801-810). Springer, Cham.
  • [4] Huang, B., Feng, G., Tang, X., Gu, J.X., Xu, G., Cattley, R., Gu, F. and Ball, A.D., 2019. A performance evaluation of two bispectrum analysis methods applied to electrical current signals for monitoring induction motor-driven systems. Energies, 12(8), p.1438.
  • [5] Shaeboub, A., Gu, F., Lane, M., Haba, U., Wu, Z. and Ball, A.D., 2017. Modulation signal bispectrum analysis of electric signals for the detection and diagnosis of compound faults in induction motors with sensorless drives. Systems Science & Control Engineering, 5(1), pp.252-267.
  • [6] Alwodai, A., Wang, T., Chen, Z., Gu, F., Cattley, R. and Ball, A., 2013. A study of motor bearing fault diagnosis using modulation signal bispectrum analysis of motor current signals. Journal of Signal and Information Processing, 4(03), p.72.
  • [7] Zhen, D., Wang, Z., Li, H., Zhang, H., Yang, J. and Gu, F., 2019. An improved cyclic modulation spectral analysis based on the CWT and its application on broken rotor bar fault diagnosis for induction motors. Applied Sciences, 9(18), p.3902.
  • [8] Wang, Z., Yang, J., Li, H., Zhen, D., Xu, Y. and Gu, F., 2019. Fault identification of broken rotor bars in induction motors using an improved cyclic modulation spectral analysis. Energies, 12(17), p.3279.
  • [9] Li, H., Wang, Z., Zhen, D., Gu, F. and Ball, A., 2019. Modulation sideband separation using the Teager–Kaiser energy operator for rotor fault diagnostics of induction motors. Energies, 12(23), p.4437.

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