Search for Author, Title, Keyword
Evaluation procedure for blowing machine monitoring and predicting bearing SKFNU6322 failure by power spectral density
More details
Hide details
Sustainable Mining Engineering Research Group. Department of Mining, Mechanic, Energetic and Construction Engineering. Higher Technical School of Engineering, University of Huelva, 21007 Huelva, Spain
Department of Water, Mining and Environment. Scientific and Technological Centre of Huelva, University of Huelva, 21007 Huelva, Spain
Publication date: 2021-09-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(3):522-529
  • Comparative study of characteristic frequencies in terms of Power Spectral Density.
  • Monitoring of blower unit and the SKFNU322 bearing.
  • A new predictive maintenance protocol has been develop.
  • The method used allows reducing from 6 control points to one.
This work shows the results of the comparative study of characteristic frequencies in terms of Power Spectral Density (PSD) or RMS generated by a blower unit and the SKFNU322 bearing. Data is collected following ISO 10816, using Emonitor software and with speed values in RMS to avoid high and low frequency signal masking. Bearing failure is the main cause of operational shutdown in industrial sites. The difficulty of prediction is the type of breakage and the high number of variables involved. Monitoring and analysing all the variables of the SKFNU322 bearing and those of machine operation for 15 years allowed to develop a new predictive maintenance protocol. This method makes it possible to reduce from 6 control points to one, and to determine which of the 42 variables is the most incidental in the correct operation, so equipment performance and efficiency is improved, contributing to increased economic profitability. The tests were carried out on a 500 kW unit of power and It was shown that the rotation of the equipment itself caused the most generating variable of vibrational energy
Artzer A, Moats M, Bender J. Removal of Antimony and Bismuth from Copper Electrorefining Electrolyte: Part I, Review. Journal of The Minerals, Metals & Materials Society 2018; 70 (10): 2033-2040,
Castilla-Gutiérrez J, Fortes JC, Pulido-Calvo I. Analysis, evaluation and monitoring of the characteristic frequencies of pneumatic drive unit and its bearing through their corresponding frequency spectra and spectral density. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2019; 21 (4): 585–591,
Castilla-Gutiérrez J, Fortes JC, Davila JM. Control and prediction protocol for bearing failure through spectral power density. Eksploatacja I Niezawodnosc – Maintenance and Reliability 2020; 22 (4): 651–657,
Chaudhry V, Kailas AV. Elastic-Plastic Contact Conditions for Frictionally Constrained Bodies Under Cyclic Tangential Loading. Journal of Tribology 2013; 136 (1): 1-17,
Cong F, Chen J, Dong G. Vibration model of rolling element bearings in a rotor-bearing system for fault diagnosis. Journal of Sound and Vibration 2013; 332 (8): 2081–2097,
Ding X, He Q, Luo N. A fusion feature and its improvement based on locality preserving projections for rolling element bearing fault classification. Journal of Sound and Vibration 2015; 335 (20): 367–383,
Gao D, Yao W, Wu T. Failure analysis on the axial-connected bolts of the thin-walled cylinder under random vibration loading. Engineering Failure Analysis 2019; 105: 756-765,
Gebraeel N, Elwany A, Pan J. Residual Life prediction sin the absence of prior degradation know ledge. IEEE Transaction and Reliability 2009; 58 (1): 106–117,
Goyal D, Choudhary A, Pabla BS, Dhami SS. Support vector machines based non-contact fault diagnosis system for bearings. Journal of Intelligent Manufacturing 2020; 31: 1275-1289,
Haque T, Korres S, Carey JT, Jacobs PW, Loos J, Franke J. Lubricant Effects on White Etching Cracking Failures in Thrust Bearing Rig Tests. Engineering Optimization 2018; 61 (6): 979-990,
Harsha SP, Nataraj C, Kankar KP. The Effect of Ball Waviness on Nonlinear Vibration Associated with Rolling Element Bearings. International Journal of Acoustics and Vibration 2006; 11 (2): 56-66,
Hernot X, Sartor M, Guillot J. Calculation of the stiffness matrix of angular contact ball bearings by using the analytical approach. Journal of Mechanical Design 2000; 122 (1): 83-90,
Houpert L. An Enhanced Study of the Load–Displacement Relationships for Rolling Element Bearings. Journal of Tribology 2014; 136 (1):1-11,
Houpert L. A Uniform Analytical Approach for Ball and Roller Bearings Calculations. Journal of Tribology 1997; 119 (4): 851-858,
Hsu JY, Wang YF, Lin KC, Chen MY, Hsu JHY. Wind Turbine Fault Diagnosis and Predictive Maintenance Through Statistical Process Control and Machine Learning 2020; IEEE Access, 8: 23427-23439.
Huang L, Huang H, Liu Y. A Fault Diagnosis Approach for Rolling Bearing Based on Wavelet Packet Decomposition and GMM-HMM. International Journal of Acoustics and Vibration 2019; 24 (2): 199-209,
Irwansyah D, Harahap MRF, Erliana CI, Abdullah D, Sari A, Siregar NA, Dangs A, Indahingwati A, Sumartono E, Wilujeng S, Nurmawati, Subekti P, Kurniasih N, Rosalina F and Hartono H. Improvement Suggestion Performance of Blowing Machine Line 4 with Total Productive Maintenance (TPM) Method at PT. Coca-Cola Amatil Indonesia Medan Unit. Journal of Physics: Conference Series 2019; 1361,
Kauschinger B, Schroeder S. Uncertainties in Heat Loss Models of Rolling Bearings of Machine Tools. Procedia CIRP 2013; 46: 107-110,
Li H, Fu L, Zheng H. Bearing fault diagnosis based on amplitude and phase map of Hermitian wavelet transform. Journal of Mechanical Science and Technology 2011; 25 (11): 2731–2740,
Louhichi R, Sallak M, Pelletan J. A Maintenance Cost Optimization Approach: Application on a Mechanical Bearing System. International Journal of Mechanical Engineering and Robotics Research 2020; 9 (5): 658-664,
Madoliat R, Ghanati MF. Theoretical and Experimental Study of Spindle Ball Bearing Nonlinear Stiffness. Journal of Mechanics 2013; 29 (4): 633-642,
Malla C, Panigrahi I. Review of Condition Monitoring of Rolling Element Bearing Using Vibration Analysis and Other Techniques. Journal of Vibration Engineering & Technologies 2019; 7: 407–414,
McFadden PD, Smith JD. Model for the vibration produced by a single point defect in a rolling element bearing. Journal of Sound and Vibration 1984; 96 (1): 69–82,
Medrano ZY, Perez C, Gomez J, Vera M. Novel Methodology of Fault Diagnosis on Bearings in a Synchronous Machine by Processing Vibroacoustic Signals Using Power Spectral Density. Ingeniería Investigación y Tecnología 2016; 17 (1): 73-85,
Mercorelli P. A denoising procedure using wavelet packets for instantaneous detection of pantograph oscillations. Mechanical Systems and Signal Processing 2013; 35 (1-2): 137–149,
Mucka P, Juraj Stein G, Tobolka P. Whole-body vibration and vertical road profile displacement power spectral density. Engineering Optimization 2019; 58 (4): 630-656,
Nagi G, Alaa E, Jing P. Residual Life prediction sin the absence of prior degradation know ledge, IEEE Transaction and Reliability 2009; 58:106–117,
Nandi S, Toliyat HA, Li X. Condition Monitoring and Fault Diagnosis of Electrical Motors-A Review. IEEE Transactions on Energy Conversion 2005; 20 (4): 719-729,
Pawlik P. Single-number statistical parameters in the assessment of the techinical condition of machines operating under variable load. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21 (1): 164-169,
Qiu H, Lee J, Lin J, Yu G. Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics. Journal of Sound and Vibration 2006; 289 (4-5): 1066–1090,
Schnabel S, Marklund P, Larsson R, Golling S. The Detection of Plastic Deformation in Rolling Element Bearings by Acoustic Emission. Tribology International 2017; 110: 209-215,
Sawalhi N, Randall RB. Helicopter gearbox bearing blind fault identification using a range of analysis techniques. Engineering Optimization 2015; 5 (2): 157-168,
Shahgoli G, Saunders C, Fielke J. Application of Power Spectral Density to Recognise the Important Factors Creating Tractor-Subsoiler Vibrations. Engineering Optimization 2015; 7 (1): 39-46,
Sun Q, Feng D, He L, Tu Y, Zhang H, Shi L. Failure analysis of cantilever bearing in wellbore trajectory control tool with high build-up rate. Engineering Failure Analysis 2019; 104: 1040-1052,
Toledo E, Pinhas I, Aravot D, Akselrod S. Bispectrum and bicoherence for the investigation of very high frequency peaks in heart rate variability. Proceedings of the IEEE Computers in Cardiology 2001; 28: 667-670,
Tse P, Peng Y, Yam R. Wavelet analysis and envelope detection for rolling element bearing fault diagnosis-Their Effectiveness and Flexibilities. Journal of Vibration and Acoustic 2001; 123 (3): 303-310,
Vitturi S. PC-based automation systems: an example of application for the real-time control of blowing machines. Computer Standars and Interfaces 2004, 24: 145-155,
Wang J, Liang Y, Zheng Y, Gao RX, Zhang F. An integrated fault diagnosis and prognosis approach for predictive maintenance of wind turbine bearing with limited samples. Renewable Energy 2020; 145: 642-650,
Wang NF, Jiang DX, Yang WG. Dual‑Tree Complex Wavelet Transform and SVD‑Based Acceleration Signals Denoising and its Application in Fault Features Enhancement for Wind Turbine. Journal of Vibration Engineering & Technologies 2019; 7: 311–320,
40 . Yeong-Maw H, Dyi-Cheng C, Gow-Yi T. Study on Asymmetrical Sheet Rolling by the Finite Element Method. Journal of Mechanics 1999; 15 (4): 149-155,
Yujie G, Jingyu L, Jie L, Zhanhui L, Wentao Z. A method for improving envelop spectrum symptom of fault rolling bearing based on the auto-correlation acceleration signal. Applied Mechanics and Materials 2013; 275-277: 856–864,
Zheng D, Chen W. Thermal performances on angular contact ball bearing of high speed spindle considering structural constraints under oilair lubrication. Tribology International 2017; 109: 593–601,
Zhou W, Habetler TG, Harley RG. Bearing Condition Monitoring Methods for Electric Machines: A General Review. IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives 2007; 3-6,
Journals System - logo
Scroll to top