Analisis Ketidaksesumbuan Poros (Misalignment) pada Rotordinamik Berdasarkan Sinyal Suara

Authors

  • Dedi Suryadi Universitas Bengkulu
  • M Reza Febriyanto Universitas Bengkulu
  • Fitrilina Fitrilina Universitas Bengkulu

DOI:

https://doi.org/10.21776/ub.jrm.2021.012.02.25

Keywords:

Misalignment, Sound Spectrum, Fast Fourier Transform, Rotor Dynamics

Abstract

This research aims to identify misalignment of the rotor dynamics based on sound spectrum characteristic. In this study, rotor dynamics consist of motor, shaft, coupling and bearings. Three types of misalignment were considered, namely parallel, angular, and combination misalignment. In order to obtain the best signal, microphones were used as sensors to capture sound signal placed on coupling and each bearing. The signal obtained was in time series. The sound signal in the time domain is then filtered to remove noise signals, which are then transferred to be signals in the frequency domain using Fast Fourier Transform (FFT). From the test results, it is found that in the case of parallel misalignment, the sound frequency spectrum is obtained with a peak amplitude at 2x rpm. The case of angular misalignment obtained a sound spectrum with a peak amplitude value and is dominant at 1x rpm than 2x rpm. Meanwhile, in the case of a combination of parallel and angular misalignment, a peak amplitude sound spectrum appears at 1x rpm and 2x rpm with relatively close spacing between the peaks of the sound spectrum. The result shows that sound signal can be used for identification of misalignment of the rotor dynamics.

Author Biography

Dedi Suryadi, Universitas Bengkulu

Teknik Mesin

References

A. HAD AND K. SABRI, “A two-stage blind deconvolution strategy for bearing fault vibration signalsâ€, Mech. Syst. Signal Process., vol. 134, p. 106307, 2019.

L. CUI, X. GONG, J. ZHANG, AND H. WANG, “Double-dictionary matching pursuit for fault extent evaluation of rolling bearing based on the Lempel-Ziv complexityâ€, J. Sound Vib., vol. 385, pp. 372–388, 2016.

F. JIA, Y. LEI, J. LIN, X. ZHOU, N. LU, “Deep neural networks: a promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive dataâ€, Mech. Syst. Signal Process. 72 (2016) 303–315.

Z. QIAO, Y. LEI, J. LIN, F. JIA, “An adaptive unsaturated bistable stochastic resonance method and its application in mechanical fault diagnosisâ€, Mech. Syst. Signal Process. 84 (2017) 731–746.

Z. GUAN, P. CHEN, X. ZHANG, X. ZHOU, AND K. LI, “Vibration analysis of shaft misalignment and diagnosis method of structure faults for rotating machineryâ€, Int. J. Performability Eng., vol. 13, no. 4, pp. 337–347, 2017.

DEDI SURYADI DAN M DICKY PRATAMA, “Desain dan Pembuatan Alat Monitoring Kerusakan Mesin Berdasarkan Level Getaranâ€, Rekayasa Mesin., vol. 11, no. 1, pp. 21–29, 2020.

A.D. NEMBHARD, J.K. SINHA, A. YUNUSA-KALTUNGO, “Experimental observations in the shaft orbits of relatively flexible machines with different rotor related faultsâ€, Measurement 75 (2015) 320–337.

RANDALL, ROBERT B, “State of the art in monitoring rotating machinery-part 1â€, Sound and vibration, Vol.38, No.3, pp.14-21, 2004.

JALAN, ARUN KR, AND A. R. MOHANTY, “Model based fault diagnosis of a rotor–bearing system for misalignment and unbalance under steady-state conditionâ€, Journal of Sound and Vibration, Vo.327, No.3, pp.604-622, 2009.

Z. GAO, C. CECATI, AND S. X. DING, “A survey of fault diagnosis and fault-tolerant techniques—Part I: Fault diagnosis with model-based and signal-based approachesâ€, IEEE Trans. Ind. Electron., vol. 62, no. 6, pp. 3757–3767, Jun. 2015.

P. A. DELGADO-ARREDONDO, D. MORINIGO-SOTELO, R. A. OSORNIO-RIOS, J. G. AVINA-CERVANTES, H. ROSTRO-GONZALEZ, AND R. DE J. ROMERO-TRONCOSO, “Methodology for fault detection in induction motors via sound and vibration signalsâ€, Mech. Syst. Signal Process., vol. 83, pp. 568–589, 2017.

D. H. SEO, J. H. JEON, AND Y. H. KIM, “A novel sensing method of fault in moving machineâ€, Mech. Syst. Signal Process., vol. 45, no. 1, pp. 154–169, 2014.

J.H. JUNG, B.C. JEON, B.D. YOUN, M. KIM, D. KIM, Y. KIM, “Omnidirectional regeneration (ODR) of proximity sensor signals for robust diagnosis of journal bearing systemsâ€, Mech. Syst. Signal Process. 90 (2017) 189–207.

A. SAPUTRA, FEBLIL HUDA, MUSTAFA AKBAR “Balancing rotor dinamik menggunakan sinyal suara,†Vol. 5, No. 1. pp. 1–8, 2018.

A. GARCIA-PEREZ, R.J. ROMERO-TRONCOSO, E. CABAL-YEPEZ, R.A. OSORNIO-RIOS, J.A. LUCIO-MARTINEZ, “Application of high-resolution spectral analysis for identifying faults in induction motors by means of soundâ€, J. Vib. Control. 18 (2011) 1585–1594.

C. VERUCCHI, J.M. BOSSIO, G.R. BOSSIO, G. ACOSTA, “Misalignment detection in induction motors with flexible coupling by means of estimated torque analysis and MCSAâ€, Mech. Syst. Signal Process.80 (2016)570-571.

SM KHOT AND PALLAVI KHAIRE. “Simulation and Experimental Study for Diagnosis of Misalignment Effect in Rotating Systemâ€, Journal of Vibration Analysis, Measurement, and Control (2015) Vol. 3 No. 2 pp. 165-17.

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Published

2021-09-08

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