Development of Dynamic Signal Analyzer Virtual Instrument (DSA VI): A Research Proposal
DOI:
https://doi.org/10.21063/jtm.2016.v6.i1.50-54Kata Kunci:
predictive maintenance, dynamic signal analyzer, computer-based virtual instrument, measured mechanical signalsAbstrak
At present, one of the maintenance types that is being developed is the predictive maintenance based on the mechanical signals obtained by performing the mechanical quantities measurements. In general, a mechanical signal is a dynamic signal where to acquire this signal, it is required a dynamic signal analyzer (DSA) instrument. However, the availability of DSA instruments in the market is limited in functionality and specification and also high cost. Therefore, in this work, a DSA instrument in the form of computer-based virtual instrument (DSA VI) would be developed. The DSA VI would designed by using the LabVIEW software and an Arduino UNO hardware. It is hopefully that the developed DSA VI capables to acquiring, processing, displaying, storing and reading the measured mechanical signals.
Referensi
S.P. Mogaland D.I. Lalwani, “A brief review on fault diagnosis of rotating machineries,”Applied Mechanics and Materials, 2014, vol. 541-542, pp. 635-640.
P. Guptaand O.P. Gandi, “Cost-down time monitoring for defect detection in rotating equipment,”International Journal of Performability Engineering, 2014, vol. 10(2), pp. 197-210.
M.Saxena, O.O.Bannett, V. SharmaandR. Khemchandani, “Fault prediction in ball bearing by using analytical wavelet transform (AWT),”International Journal of Scientific and Engineering Research, 2014, vol. 658, pp. 289-294.
S.Khanam, N.TandonandJ.K. Dutt,“Fault size estimation in the outer race of ball bearing using discrete wavelet transform of the vibration signal,” The2nd International Conference on Innovations in Automation and Mechatronics Engineering (ICIAME),2014, pp. 12-19.
B. CarmenandB. Florin, “Bearing scuffing detection and condition monitoring using virtual instrumentation,”Applied Mechanics and Materials, 2014, vol. 657, pp. 604-608.
A.J. KumbharandN.K. Chhapkhane, “Detection of the distributed defects on Inner and outer race of ball bearing using vibration analysis,”International Journal of Engineering Research and Technology (IJERT), 2014, vol. 3(11), pp. 147-150.
B.Carmen, M. RazvanandO.N. Dumitru, “Study on the defects size of ball bearings elements using vibration analysis,”Applied Mechanics and Materials, 2014, vol. 658, pp. 289-294.
W.Shuqian, M.Mei, Z. Jingling, Z. WeinanandW. Guoqing, “Vibration test of bearing ball fatigue testing machine base on VB,”Applied Mechanics and Materials, 2014, vol. 607, pp. 523-526.
D.S. ShahandV.N. Patel, “A review of dynamic modeling and fault identifications methods for rolling element bearing,”in The2nd International Conference on Innovations in Automation and Mechatronics Engineering (ICIAME),2014,pp. 447-456.
M. YuzukirmiziandH. Arslan, “Fault diagnosis of shaft-ball bearing system using one-way analysis of variance,”Mathematical and Computational Applications, 2014, vol. 19(1), pp. 37-49.
C.H.Chen, R.J. ShyuandC.K.Ma, “A new fault diagnosis method of rotating machinery,”Shock and Vibration, 2008, vol. 15, pp. 585-598.
H.Yang, J. MathewandL. Ma, “Intelligent Diagnosis of Rotating Machinery Faults-A Review,”in The 3rd Asia-Pacific Conference on Systems Integrity and Maintenance (ACSIM), 2002, 25-27 September 2002, Cairns, Australia.
E.Swanson, C.D. PowelandS. Weissman, “A practical Review of Rotating Machinery Critical Speeds and Modes,”Sound and Vibration, 2005, vol. 162(3), pp. 471-487.
S.H. Ghafari, A Fault Diagnosis System for Rotary Machinery Supported by Rolling Element Bearings, 2007, University of Waterloo: PhD theses.
S.H.Ghafari, F.GolnaraghiandF. Ismail, “Fault diagnosis based on chaotic vibration of rotor systems Supported by Ball Bearings,”in The Proceeding of COMADEM, 2006, pp. 819-826.
F.K.Choy, J.Zhou, M.J.BraunandL.Wang, “Vibration monitoring and damage quantification of faulty ball bearings,”Tribology, 2005, vol. 127(4), pp. 776-783.
T.Williams, X.Ribadeneira, S.BillingtonandT. Kurfesss, “Rolling element bearing diagnostics in run-to-failure lifetime testing,”Mechanical Systems and Signal Processing, 2001, vol. 15(5), pp. 979-993.
B. Mevel andJ.L. Guyader, “Routes to chaos in ball bearings,”Sound and Vibration, 1993, vol. 162(3), pp. 471-487.
D. Kanneg andW. Wang, “A Wavelet Spectrum Technique for Machinery Fault Diagnosis,”Journal of Signal and Information Processing, 2011, vol. 2, pp. 322-329.
A. Yoshihiro, M. Satoru, andK. Shinji, “Online Monitoring Technologyby nalysis of Highly Accurate Vibration Waveform to Diagnose Abnormality of Machines,”JFE Technical Report,2012, vol. 17, pp. 17–22.
A.Yoshihiro, M. Satoru, andK. Shinji, “Multi-function Online Monitoring (Condition-eye),” JFE Giho, 2011, vol. 27, pp. 58–60.
W. Niu, “Fault diagnosis for rotator in rotating machinery based on support vector machine,”Applied Mechanics and Materials, 2014, vol. 532, pp.102-105.
C. Yue, X. Ren, Y. YangandW. Deng, “Unbalance Identification of Speed-Variant Rotary Machinery without Phase Angle Measurement,”Shock and Vibration, 2015, vol. 62(3), pp. 463-471.
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