Abstract
Preventive maintenance is one of the main concerns in modern industry, in which early failure detection increases the lifecycle of machines. In this paper, electrical signature analysis is employed to indicate the development or existence of faults within the proposed system and this is achieved by embedding a real-time frequency analysis of the motor current. The term in the title electrical signature analysis basically refers to the motor current or voltage attributes are being used as a transducers to detect the changes in their spectrum in both the conditions; healthy and unhealthy. The algorithm used for analyzing the signals in frequency domain is done using Fast Fourier transform. In this work, we have focused on failure of bearing part of single phase induction motor and developed hardware for monitoring conditions (i.e. health of the motor) in run time. Because of the simplicity of this technique the mechanism of fault diagnosis is employed using an FPGA approach that offers re-configurability. This work can be very useful in industrial setup where there are 100 motors working together for some production lines. The findings show promising results which could lead to better reliability performance of the induction motor and lower maintenance costs.
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Mehta VK, Mehta R (2009) Principal of electrical engineering. Single phase transformer. S. Chand & Company Pvt. Ltd., New Delhi, pp 419–437
Sattar A, Hussain I, Memon TD, Karar H, Saeed U (2016) Investigation of imbalance faults in horizontal axis WTGS through analysis of generator current signal. Indian J Sci Technol. https://doi.org/10.17485/ijst/2016/v9i47/108654
Soomro AA, Hussain I, Kazi K, Khoso SK, Ansari S (2016) A hybrid monitoring technique for diagnosis of mechanical faults in induction motor. Indian J Sci Technol 9:47
Hussain I, Abro FR, Khizer AN, Ali H (2015) Fault detection and identification in horizontal axis wind turbine using current signal analysis. Sindh Univ Res J Sci Ser 47(2):291–294
Othman MS, Nuawi MZ (2015) Vibration and acoustic emission signal monitoring for detection of induction motor bearing fault 4(05):924–929
Musavi SHA, Chowdhry BS, Kumar T, Pandey B, Kumar W (2015) IoTs enable active contour modeling based energy efficient and thermal aware object tracking on FPGA. Wirel Personal Commun 85(2):529–543
Garcia-Perez A, Romero-Troncoso R, Cabal-Yepez E, Osornio-Rios R, Rangel-Magdaleno J, Miranda H (2011) Startup current analysis of incipient broken rotor bar in induction motors using high-resolution spectral analysis. In: Proceedings of IEEE international symposium on diagnosis for electrical machines, power electronics and drives, Sep. 2011, pp 657–663
Cristaldi L, Faifer M, Lazzaroni M, Toscani S (2009) An inverter-fed induction motor diagnostic tool based on time-domain current analysis. IEEE Trans Instrum Meas 58(5):1454–1461
Deekshit Kompella KC, Rao MV, Rao RS, Sreenivasu R (2013) Estimation of nascent stage bearing faults of induction motor by stator current signature using adaptive signal processing. In: Proceedings of IEEE INDICON, December (2013), pp 1–5
Zhou W, Lu B, Ghabetler T, Ronald Harley G (2009) Incipient bearing fault detection via motor stator current noise cancellation using Wiener filter. IEEE Trans Ind Appl 45(July/August (4)):1309–1317
Obaid RR, Habetler TG, Stack JR (2003) Stator current analysis for bearing damage detection in induction motors. In: Proceedings of 4th IEEE SDEMPED, August (2003), pp 182–187
Hu NQ, Xia LR, Gu FS, Qin GJ (2011) A novel transform demodulation algorithm for motor incipient fault detection. IEEE Trans Instrum Meas 60(2):480–487
Verification D, Timing S (2005) Xilinx ISE 8 software manuals and help-PDF collection. Interfaces (Providence). Xilinx, Inc., no. c, pp 1–14
PedroniVA (2004) Circuit design with VHDL, XIV
Memon T, Baig S, Kalwar IH, Deshi M (2017) SWL algorithms optimization using alternative adder module in FPGA. 6th Mediterranean conference on embedded computing (MECO), Bar Montenegro, 11–15 June 2017
Alsaedi MA (2015) Fault diagnosis of three-phase induction motor: a review. Appl Optics Signal Proc 4(3):1–8
Shaikh F, Imtiaz Hussain T, Memon D (2017) Design and analysis of linear phase FIR filter in FPGA using PSO Algorithm. 6th Mediterranean conference on embedded computing (MECO), Bar Montenegro, 11–15 June 2017
Shaikh UT, Memon TD, Kalwar IH, Shaikh F (2017) Design of IIR filter using PSO algorithm and its implementation in FPGA. 3rd international conference on green computing and engineering technologies, (ICGCET®) 8th to 10th August 2017 Killaloe, Ireland
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Karim, E., Memon, T.D. & Hussain, I. FPGA based on-line fault diagnostic of induction motors using electrical signature analysis. Int. j. inf. tecnol. 11, 165–169 (2019). https://doi.org/10.1007/s41870-018-0238-5
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DOI: https://doi.org/10.1007/s41870-018-0238-5