Software development firmware system for broken rotor bar detection and diagnosis of induction motor through current signature analysis

Authors

  • H. Pita Laboratory of Industrial Innovation Technology and Robotics (LITIR), Faculty of Engineering and Architecture, Universidad Privada Boliviana (UPB), Cochabamba, Bolivia.
  • G. Zurita Laboratory of Industrial Innovation Technology and Robotics (LITIR), Faculty of Engineering and Architecture, Universidad Privada Boliviana (UPB), Cochabamba, Bolivia
  • A. Villarroel Laboratory of Industrial Innovation Technology and Robotics (LITIR), Faculty of Engineering and Architecture, Universidad Privada Boliviana (UPB), Cochabamba, Bolivia

DOI:

https://doi.org/10.15282/jmes.14.2.2020.30.0542

Keywords:

Motor of current signature analysis, test bench, fast fourier transform, envelope analysis, broken rotor bars, firmware

Abstract

The induction motors (IMs) are undoubtedly the most used machines in industries because of the advantages they offer such as simplicity, service continuity and low cost. Due to wear and tear, the motor suffers different types of mechanical and electrical failures. Depending on the criticality of the plant motors, it could be necessary to implement predictive techniques in order to detect the faults before they can cause unnecessary downtime. Therefore, in this paper, the research approach was to develop a low cost measurement system based on a micro controller platform for machine diagnosis. The FRDM K64F developing board was selected as the most suitable for satisfying the system conditions, and it was used to collect induction motor`s current data. In order to validate the accuracy of the developed system, the Frequency Transfer Functions (FRF) of the developed measurement system and the standard system (NI USB-6009) were compare. It showed a flat frequency spectrum from 0 to 1 KHz, with small fluctuations of about 0.25 dB standard deviation. A fully automated test bench was implemented, which allows to perform all the measurement tests with the IMs, and in this case, the detection and diagnosis of broken bars. Around 240 tests were performed with varying loads, different rotation speeds, and with different severity damage levels in the rotor. The data analysis procedure for broken rotor bar detection and motor diagnosis was performed by the Motor Current Signature Analysis (MCSA), FFT and Enveloped Analysis (EA). Finally, the research approach was successfully accomplished, by the team by developing a software firmware measurement ultra-low cost development platform for machine diagnosis. It was also developed a proper antialiasing filter to reduce industrial noise. The effectiveness of the proposed system is detecting a weak fault in a noise signal. It was found out a new consistent and robust parameter called the pole pass frequency (fpsf), which could be used as a diagnosis parameter for detection of broken rotor bars faults, with their damage severity degree. The detected parameter can be found around 2.6 Hz, and it increases in amplitude with increasing damage severity.

References

N. S. Toliya H.A, “Novel frequency domain based technique to detect incipient stator inter-turn faults in induction machines,” Ind. Appl. Conf., vol. vol.1, no., 2000.

R. Bond, Vibration-based condition monitoring. Wiley, 2011.

J. Cibulka, M. K. Ebbesen, G. Hovland, K. G. Robbersmyr, and M. R. Hansen, “Review on Approaches for Condition Based Maintenance in Applications with Induction Machines located Offshore,” Model. Identif. Control A Nor. Res. Bull., vol. 33, no. 2, pp. 69–86, Sep. 2012, doi: 10.4173/mic.2012.2.4.

A. S. M. Silahuddin, A. M. Aizuddin, S. Mohamaddan, S. T. Syed Shazali, M. S. Z. M. Suffian, A. M. Tazuddin, “Design and development of a modular vibration test rig for combination types of fault in rotating machinery health diagnosis,” J. Mech. Eng. Sci., vol. Vol 13.

P. Shi, Z. Chen, Y. Vagapov, and Z. Zouaoui, “A new diagnosis of broken rotor bar fault extent in three phase squirrel cage induction motor,” Mech. Syst. Signal Process., vol. 42, no. 1–2, pp. 388–403, Jul. 2014, doi: 10.1016/j.ymssp.2013.09.002.

H. H. Kryter, RC., “Electrical signature analysis applications for non-intrusive automotive alternator diagnostics,” Meet. Soc. Mach. Fail. Prev. Technol., 1996.

V. F. Pires, M. Kadivonga, J. F. Martins, and A. J. Pires, “Motor square current signature analysis for induction motor rotor diagnosis,” Measurement, vol. 46, no. 2, pp. 942–948, Jul. 2013, doi: 10.1016/j.measurement.2012.10.008.

V. Hegde and G. S. Maruthi, “Experimental investigation on detection of air gap eccentricity in induction motors by current and vibration signature analysis using non-invasive sensors,” Energy Procedia, vol. 14, pp. 1047–1052, Jul. 2012, doi: 10.1016/j.egypro.2011.12.1053.

A. Roque, J. M. F. Calado, and J. M. Ruiz, “Vibration Analysis versus Current Signature Analysis,” IFAC Proc. Vol., vol. 45, no. 20, pp. 794–799, Jul. 2012, doi: 10.3182/20120829-3-MX-2028.00286.

V. Dlamini, R. Naidoo, and M. Manyage, “A non-intrusive method for estimating motor efficiency using vibration signature analysis,” Int. J. Electr. Power Energy Syst., vol. 45, no. 1, pp. 384–390, Jul. 2013, doi: 10.1016/j.ijepes.2012.09.015.

G. Kumar, S. Sharma, and H. Malik, “Learning Vector Quantization Neural Network Based External Fault Diagnosis Model for Three Phase Induction Motor Using Current Signature Analysis,” Procedia Comput. Sci., vol. 93, pp. 1010–1016, Jul. 2016, doi: 10.1016/j.procs.2016.07.304.

L. Eren, M. Aşkar, and M. J. Devaney, “Motor current signature analysis via four-channel FIR filter banks,” Measurement, vol. 89, pp. 322–327, Jul. 2016, doi: 10.1016/j.measurement.2016.04.025.

M. Abd-el-Malek, A. K. Abdelsalam, and O. E. Hassan, “Induction motor broken rotor bar fault location detection through envelope analysis of start-up current using Hilbert transform,” Mech. Syst. Signal Process., vol. 93, pp. 332–350, Jul. 2017, doi: 10.1016/j.ymssp.2017.02.014.

S. Aouabdi, M. Taibi, S. Bouras, and N. Boutasseta, “Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis,” Mech. Syst. Signal Process., vol. 90, pp. 298–316, Jul. 2017, doi: 10.1016/j.ymssp.2016.12.027.

I. Bravo-Imaz, H. Davari Ardakani, Z. Liu, A. García-Arribas, A. Arnaiz, and J. Lee, “Motor current signature analysis for gearbox condition monitoring under transient speeds using wavelet analysis and dual-level time synchronous averaging,” Mech. Syst. Signal Process., vol. 94, pp. 73–84, Jul. 2017, doi: 10.1016/j.ymssp.2017.02.011.

P. Bilski and W. Winiecki, “A low-cost real-time virtual spectrum analyzer,” IEEE Trans. Instrum. Meas., vol. 56, no. 6, pp. 2169–2174, 2007, doi: 10.1109/TIM.2007.908269.

M. K. Adeyeri, K. Mpofu, and B. Kareem, “Development of hardware system using temperature and vibration maintenance models integration concepts for conventional machines monitoring: a case study,” J. Ind. Eng. Int., vol. 12, no. 1, pp. 93–109, 2016, doi: 10.1007/s40092-015-0132-8.

H. F. Zhang and W. Kang, “Design of the data acquisition system based on STM32,” Procedia Comput. Sci., vol. 17, pp. 222–228, 2013, doi: 10.1016/j.procs.2013.05.030.

G. Huang and Y. Fan, “Design and realization of vibration signal acquisition & analysis system based on STM32,” 2016, pp. 2924–2928, doi: 10.1109/CCDC.2016.7531482.

S. J. Hester J, Prabhu, S, atamturktur S, “Remote and wireless long term vibration monitoring of historic monuments.,” Procedia Eng., vol. 168, no. 3302–3307, 2017.

M. F. Herrasti Z, Gabilondo I, Berganzo J, Val I., “Wireless sensor nodes for acceleration strain and temperature measurements,” Procedia Eng., pp. 1659–1662, 2016.

A. Villarroel, G. Zurita, and R. Velarde, “Development of a low-cost vibration measurement system for industrial applications,” Machines, vol. 7, no. 1, 2019, doi: 10.3390/machines7010012.

E. P. Carden and P. Fanning, “Vibration Based Condition Monitoring: A Review,” Struct. Heal. Monit. An Int. J., vol. 3, no. 4, pp. 355–377, Sep. 2004, doi: 10.1177/1475921704047500.

Z. Dragomir OE, Gouriveau R, Dragomir F, Minca E, “Review of prognostic problem in condition-based maintenance.,” in 2009 European Control Conference (ECC). IEEE:, 2009, pp. 1587–1592.

A. Prajapati, J. Bechtel, and S. Ganesan, “Condition based maintenance: a survey,” J. Qual. Maint. Eng., vol. 18, no. 4, pp. 384–400, Sep. 2012, doi: 10.1108/13552511211281552.

H. P. Ruben P, Manuel P, Martin R, Jose F, “Improved resolution of the MCSA method via Hilbert transform. enabling the diagnosis of rotor asymetries at lower slip.,” IEEE Trans. Energy Convers. 2009;, vol. 24, pp. 52–59, 2009.

H. H. Kryter R, “Condition monitoring of machinery using motor current signature analysis.,” J. Sound Vib., vol. 23, pp. 14–21, 1989.

S. O., Digital Signal Processing. Pearson, 2015.

A. B. Ming, W. Zhang, Z. Y. Qin, and F. L. Chu, “Envelope calculation of the multi-component signal and its application to the deterministic component cancellation in bearing fault diagnosis,” Mech. Syst. Signal Process., vol. 50–51, pp. 70–100, Jul. 2015, doi: 10.1016/j.ymssp.2014.05.033.

M. A. S. M. Tahir, J. A. Ghani, M. Z. Nuawi, M. Rizal, and C. H. C. Haron, “Flank wear and I-kaz 3D correlation in ball end milling process of Inconel 718,” J. Mech. Eng. Sci., vol. 9, no. December, pp. 1595–1603, 2015, doi: 10.15282/jmes.9.2015.7.0155.

journal.ump.edu.my/jmes ◄

H. M. Rizal1, J.A. Ghani, Husni, “Design and construction of a strain gauge-based dynamometer for a 3-axis cutting force measurement in turning process,” J. Mech. Eng. Sci., vol. 12, no. 4, 2018.

S. R. Blomqvist KH, Eskelinen P, “Instrumentation amplifier implements second-order active low-pass filter with high gain factor.,” Meas. Sci. Technol., vol. 22, 2011.

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Published

2020-06-23

How to Cite

[1]
H. Pita, G. Zurita, and A. Villarroel, “Software development firmware system for broken rotor bar detection and diagnosis of induction motor through current signature analysis”, J. Mech. Eng. Sci., vol. 14, no. 2, pp. 6917–6933, Jun. 2020.

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