A Review on Fault Diagnosis of Misaligned Rotor Systems

doi:10.23940/ijpe.20.04.p1.499509

Abstract

Abstract:

The diagnosis and prognosis of misaligned rotor systems have gained importance in recent times. Misalignment has become one of the main reasons for system vibration, which reduces the life and stability of machine parts, making it vitally important for machines to perform effectively without any catastrophic failure. Limited research has been reported on understanding its effect on rotor systems. Even if zero misalignment is achieved at the beginning, it cannot be retained over longer durations due to various reasons. Many techniques like DWT, CWT, and HHT are also used to understand the misalignment problem. Some advanced techniques such as MCSA, thermal imaging, and the acoustic emission technique have come into existence and become important tools to classify faults, leading to more reliable misalignment diagnosis. In the present study, a detailed literature review is conducted to diagnose and classify misalignments. All recent techniques and their limitations are discussed, and a hybrid approach is presented for the lucid understanding of this fault and its classification.

Key words: machinery condition monitoring, misalignment, signal based techniques, fault diagnosis, mathematical modeling

Kumar Jalan Arun, Patil Shital, and Mittal Gaurav. A Review on Fault Diagnosis of Misaligned Rotor Systems [J]. Int J Performability Eng, 2020, 16(4): 499-509.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

References 97.

1.	J. R. Mancuso, “The Manufacturers World of Coupling Potential Unbalance,” inProceedings of the Thirteenth Turbomachinery Symposium, pp. 97-103, 1985
2.	T. Y.Wu and Y. L. Chung, “Misalignment Diagnosis of Rotating Machinery Through Vibration Analysis via the Hybrid EEMD and EMD Approach,” Smart Materials and Structures, Vol. 18, No. 9, 2009
3.	S. Jesse, J. W. Hines, A. Edmondson,D. Nower, “Motor Shaft Misalignment Bearing Load Analysis,” in Proceedings of the Maintenance and Reliability Conference (MARCON 99), Gatlinburg TN, 1999
4.	V. Hariharan and PSS. Srinivasan, “Vibration Analysis of Parallel Misaligned Shaft with Ball Bearing System,” Journal of Science and Technology, Vol. 9, No. 2, pp. 45-50, 2009
5.	“A Practical Guide to Shaft Alignment,” Pruftechnik Ltd., U.S., 2002
6.	K. M.Al-Hussain, “Dynamic Stability of Two Rigid Rotors Connected by a Flexible Coupling with Angular Misalignment,”Journal of Sound and Vibration, Vol. 266, pp. 217-234, 2003
7.	O. Janssens, L. Verledens, R. Schulz, V. Ongenae, K. Stockman, M. Loccufier, et al., “Infrared and Vibration-based Bearing Fault Detection using Neural Networks,” inProceedings of 13th International Workshop on Advanced Infrared Technology and Applications, pp. 232-236, 2015
8.	M. A. Hili, T. Fakhfakh,M. Haddar, “Failure Analysis of a Misaligned and Unbalanced Flexible Rotor,” Journal of Failure Analysis and Prevention, Vol. 6, No. 4, pp. 73-82, 2006
9.	GNDS. Sudhakar and A. S. Sekhar, “Coupling Misalignment in Rotating Machines: Modeling, Effects and Monitoring,” Noise and Vibration Worldwide, Vol. 40, No. 1, pp. 17-39, 2009
10.	D. P. Behera, R. Behera,V. N. A.Naikan, “Virtual Fault Simulation for Diagnosis of Shaft Misalignment of Rotating Machine,” inProceedings of International Conference on Advances in Computing, Communications and Informatics, pp. 2476-2480, New Delhi, India, 2014
11.	J. Piotrowski, “Shaft Alignment Handbook,” Marcel Dekker Inc., New York, 1995
12.	S. Kumar, “Vibration Signature Analysis of 4 Jaw Flexible Coupling Considering Misalignment in Two Planes,” International Research Journal of Engineering and Technology (IRJET), Vol. 2, No. 1, pp. 73-84, 2015
13.	M. C. S.Reddy and A. S. Sekhar, “Detection and Monitoring of Coupling Misalignment in Rotors,” Measurement, Vol. 61, pp. 111-122, February 2015
14.	V. P. Raj, K. Natarajan,S. Girikumar, “Induction Motor Fault Detection and Diagnosis by Vibration Analysis using MEMS Accelerometer,” inProceedings of International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications (C2SPCA), pp. 1-6, Bangalore, India, 2013
15.	J. K.Sinha and K. Elbhbah, “A Future Possibility of Vibration-based Condition Monitoring of Rotating Machines,”Mechanical Systems and Signal Processing, Vol. 34, pp. 231-240, 2013
16.	S. Zhang, J. Mathew, L. Ma, Y. Sun,A. Mathew, “Statistical Condition Monitoring based on Vibration Signals,” inProceedings of VETOMAC-3 and ACSIM-2004, pp. 1238-1243, 2004
17.	T. H.Patel and A. K. Darpe, “Experimental Investigations on Vibration Response of Misaligned Rotors,”Mechanical Systems and Signal Processing, Vol. 23, pp. 2236-2252, 2009
18.	S. P.Mogal and D. I. Lalwani, “Experimental Investigation of Unbalance and Misalignment in the Rotor-Bearing System using Order Analysis,” Journal of Measurements in Engineering, Vol. 3, No. 4, pp. 114-122, 2015
19.	S. N. Ganeriwala, Z. Li,M. H. Richardson, “Using Operating Deflection Shapes to Detect Misalignment in Rotating Equipment,” IMAC XXVI, 2008
20.	N. H.Chandra and A. S. Sekhar, “Fault Detection in Rotor-Bearing Systems using Time-Frequency Techniques,”Mechanical Systems and Signal Processing 72-73, pp. 105-133, 2006
21.	N. K. Hsieh, W. Y. Lin,H. T. Young, “High-Speed Spindle Fault Diagnosis with the Empirical Mode Decomposition and Multiscale Entropy Method,” Entropy, Vol. 17, No. 4, pp.21702183, 2015
22.	J. Gertler, “Residual Generation in Model-based Fault Diagnosis,” Control Theory and Advanced Technology, Vol. 9, No. 1, pp. 259-285, 1993
23.	S. Haroun, A. N. Seghir, S. Touati,S. Hamdani, “Misalignment Fault Detection and Diagnosis using AR Model of Torque Signal,” inProceedings of IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics, and Drives, pp. 322-326, Guarda, Portugal, 2015
24.	E. Kramer, “Dynamics of Rotors and Foundations,” Springer-Verlag, New York, 1993
25.	H. D.Nelson and S. H.Crandall, “Analytic Prediction of Rotor Dynamic Response,” Ehrich, F. F., Handbook of Rotor Dynamics 2, pp. 2.1-2.84, 1992
26.	H. D.Nelson and J. M. McVaugh, “The Dynamics of Rotor-Bearing Systems using Finite Elements,”ASME Journal of Engineering for Industry, pp. 593-600, 1976
27.	B. C. Gibbons, “Coupling Misalignment Forces,” inProceedings of 5th Turbomachinery Symposium, Gas Turbine Laboratories in A&M University, Texas, pp. 111-116, 1976
28.	P. Armugam, S. Swarnamani,B. S. Prabhu, “Effects of Coupling Misalignment on the Vibration Characteristics of a Two-Stage Turbine Rotor,” in Proceedings of ASME Design Engineering Technical Conferences, Vol. 84, No. 2, pp. 1049-1054, 1995
29.	A. S.Sekhar and B. S. Prabhu, “Effects of Coupling Misalignment on Vibrations of Rotating Machinery,” Journal of Sound and Vibration, Vol. 185, No. 4, pp. 655-671, 1995
30.	Y. S.Lee and C. W. Lee, “Modelling and Vibration Analysis of Misaligned Rotor- Ball Bearing Systems,” Journal of Sound and Vibration, Vol. 224, No. 1, pp. 17-32, 1999
31.	R. Isermann, “Fault Diagnosis of Machines via Parameter Estimation and Knowledge Processing-Tutorial Paper,” Automatica, Vol. 29, No. 4, pp. 815-835, 1993
32.	A. K.Jalan and A. R. Mohanty, “Model-based Fault Diagnosis of Rotor System,” International Journal of Performability Engineering, Vol. 7, No. 6, pp. 515-523, 2011
33.	A. S. Sekhar, “Crack Identification in a Rotor System: A Model-based Approach,”Journal of Sound and Vibration, Vol. 270, pp. 887-902, 2004
34.	A. S. Sekhar, “Multiple Cracks Effects and Identification,”Mechanical Systems and Signal Processing, Vol. 22, pp. 845-878, 2008
35.	A. K.Jalan and A. R. Mohanty, “Model-based Fault Diagnosis of a Rotor-Bearing System for Misalignment and Unbalance under Steady-State Condition,”Journal of Sound and Vibration, Vol. 327, pp. 604-622, 2009
36.	N. Bachschmid, P. Pennacchi,A. Vania, “Identification of Multiple Faults in Rotor Systems,” Journal of Sound and Vibration, Vol. 254, No. 2, pp. 327-366, 2002
37.	S. Haroun, A. N. Seghir, S. Hamdani,S. Touati, “AR Model of the Torque Signal For Mechanical Induction Motor Faults Detection and Diagnosis,”Control, Engineering and Information Technology (CEIT), pp. 1-5, 2015
38.	M. Lal and R. Tiwari, “Experimental Identification of Shaft Misalignment in a Turbo-Generator System,” Indian Academy of Sciences, Sadhana, Vol. 43, No. 80, 2018
39.	P. Pennacchi and A. Vania, “Diagnosis and Model-based Identification of a Coupling Misalignment,”Shock and Vibration, Vol. 12, pp. 293-308, 2005
40.	GNDS. Sudhakar and A. S. Sekhar, “Coupling Misalignment in Rotating Machines: Modeling, Effects and Monitoring,” Noise and Vibration Worldwide, Vol. 40, No. 1, pp. 17-39, 2009
41.	A. K.Jalan and A. R. Mohanty, “Model-based Fault Identification of Unbalance and Misalignment Simultaneously Present in a Rotor System,” Advances in Vibration Engineering, Vol. 12, No. 1, pp. 23-32, 2013
42.	O. A. Omitaomu, A. B. Badiru,J. W. Hines, “On-Line Prediction of Motor Shaft Misalignment using Fast Fourier Transform Generated Spectra Data and Support Vector Regression,”Transactions of ASME - Journal of Manufacturing Science and Engineering, Vol. 128, pp. 1019-1024, 2006
43.	A. K. Verma, S. Sarangi,M. H. Kolekar, “Shaft Misalignment Detection using Stator Current Monitoring,”International Journal of Advanced Computer Research, Vol. 3, pp. 305-309, 2013
44.	D. L.Dewell and L. D. Mitchell, “Detection of a Misaligned Disc Coupling using Spectrum Analysis,”Transactions of ASME, Journal of Vibration, Acoustics, Stress, and Reliability in Design, Vol. 106, pp. 9-15, 1984
45.	M. A. Jordan, “What are Orbit Plots, Anyways?,” pp. 8-15, 1993
46.	R. R. Obaid, T. G. Habetler,R. M. Tallam, “Detecting Load Unbalance and Shaft Misalignment using Stator Current in Inverter Driven Induction Motors,”IEEE IEMDC, Vol. 3, pp. 1454-1458, 2013
47.	R. R.Obaid and T. G. Habetler, “Current based Algorithm for Mechanical Fault Detection in Induction Motors with Arbitrary Load Conditions,”IEEE, pp. 1347-1351, 2003
48.	C. Kumar, G. Krishnan,S. Sarangi, “Experimental Investigation on Misalignment Fault Detection in Induction Motors using Current and Vibration Signature Analysis,” inProceedings of 1st International Conference on Futuristic trend in Computational Analysis and Knowledge Management, pp. 61-66, 2015
49.	A. Umbrajkaar and A. Krishnamoorthy, “Shaft Misalignment Prediction on the Basis of Discrete Wavelet transform,” IJMET, Vol. 9, No. 7, pp. 336-344, 2018
50.	M. Monte, F. Verbelen,B. Vervisch, “Detection of Coupling Misalignment by Extended Orbits,” inProceedings of Conference on the Society for Experimental Mechanics Series, pp. 243-250, 2015
51.	J. J.Carbajal-Hernández, L. P. Sánchez-Fernandez, I. Hernández-Bautista, J. J. Medel-Juárez, and L. A. Sánchez-Pérez, “Classification of Unbalance and Misalignment in Induction Motors using Orbital Analysis and Associative Memories,”Neurocomputing, Vol. 175, pp. 838-850, 2016
52.	L. Arebi, F. Gu, N. Hu,A. Ball, “Misalignment Detection using a Wireless Sensor Mounted on a Rotating Shaft,” inProceedings of the 24th International Congress on Condition Monitoring and Diagnostics Engineering Management, pp. 1289-1299, Stavanger, Norway, 2011
53.	C. D. Costa, R. S.Da Gama, C. E. Nascimento, I. M. Brandão, E. C. De Medeiros, and M. H. Mathias, “Orbit Analysis for Imbalance Fault Detection In Rotating Machinery,” IOSR Journal of Electrical and Electronics Engineering, Vol. 13, No. 1, pp. 43-53, 2018
54.	L. Arebi, F. Gu,A. Ball, “A Comparative Study of Misalignment Detection using a Novel Wireless Sensor with Conventional Wired Sensors,” in Proceedings of 25th International Congress on Condition Monitoring and Diagnostic Engineering, Journal of Physics: Conference Series, Vol. 364, No. 1, 2012
55.	J. C.Chan and P. W. Tse, “A Novel, Fast, Reliable Data Transmission Algorithm for Wireless Machine Health Monitoring,” IEEE Transactions on Reliability, Vol. 58, No. 2, pp. 295-304, 2009
56.	L. Arebi, F. Gu,A. Ball, “Rotor Misalignment Detection using a Wireless Sensor and a Shaft Encoder,” inProceedings of Computing and Engineering Researchers' Conference, University of Huddersfield: CEARC'10, pp. 6-13, Huddersfield, 2010
57.	X. F.Fan and M. J. Zuo, “Gearbox Fault Detection using Hilbert and Wavelet Packet Transform,”Mechanical Systems and Signal Processing, Vol. 20, pp. 966-982, 2006
58.	P. Jayaswal, S. N. Verma,A. K. Wadhwani, “Application of ANN, Fuzzy Logic and Wavelet Transform in Machine Fault Diagnosis using Vibration Signal Analysis,” Journal of Quality in Maintenance Engineering, Vol. 16, No. 2, pp. 190-213, 2010
59.	F. Al-Badour, M. Sunar,L. Cheded, “Vibration Analysis of Rotating Machinery using Time-Frequency Analysis and Wavelet Techniques,”Mechanical Systems and Signal Processing, Vol. 25, pp. 2083-2101, 2011
60.	Z. K.Peng and F. L. Chu, “Application of the Wavelet Transform in Machine Condition Monitoring and Fault Diagnostics: A Review with Bibliography,”Mechanical Systems and Signal Processing, Vol. 18, pp. 199-221, 2004
61.	F. Hemmati, W. Orfali,M. S. Gadala, “Roller Bearing Acoustic Signature Extraction by Wavelet Packet Transform, Applications in Fault Detection and Size Estimation,” Applied Acoustics, Vol. 104, pp. 101-118, 2016
62.	X. Lou and K. A. Loparo, “Bearing Fault Diagnosis based on Wavelet Transform and Fuzzy Inference,”Mechanical Systems and Signal Processing, Vol. 18, pp. 1077-1095, 2004
63.	A. Umbrajkaar and A. Krishnamoorthy, “Shaft Misalignment Prediction on the Basis of Discrete Wavelet Transform,”IJMET, Vol. 9, pp. 336-344, 2018
64.	A. Umbrajkaar and A. Krishnamoorthy, “Vibration Analysis using Wavelet Transform and Fuzzy Logic for Shaft Misalignment,” Journal of Vibroengineering, Vol. 20, No. 8, pp. 336-344, 2018
65.	N. H.Chandra and A. S. Sekhar, “Detection and Monitoring of Shaft Misalignment in Rotors using Hilbert Huang Transform,” inProceedings of ASME Turbo Expo 2014: Turbine Technical Conference and Exposition 7A, 2014
66.	H. Zheng, Z. Li,X. Chen, “Gear Fault Diagnosis based on Continuous Wavelet Transform,” Mechanical Systems and Signal Processing, Vol. 16, No. 2, pp. 447-457, 2002
67.	G. R. Rameshkumar, B. V. A.Rao, and K. P. Ramachandran, “Prediction of Coast Down Time for Mechanical Faults in Rotating Machinery using Artificial Neural Networks,” International Journal of Mechanical and Mechatronics Engineering, Vol. 5, No. 3, pp. 559-566, 2011
68.	J. L. F.Chacon, E. A. Andicoberry, V. Kappatos, G. Asfis, T. H. Gan, and W. Balachandran, “Shaft Angular Misalignment Detection using Acoustic Emission,”Applied Acoustics, Vol. 85, pp. 12-22, 2014
69.	N. Tandon, G. S. Yadava,K. M. Ramakrishna, “A Comparison of Some Condition Monitoring Techniques for the Detection of a Defect in Induction Motor Ball Bearings,”Mechanical Systems and Signal Processing, Vol. 21, pp. 244-256, 2007
70.	P. Jayaswal, A. K. Wadhwani,K. B. Mulchandani, “Machine Fault Signature Analysis,” International Journal of Rotating Machinery, pp. 1-10, 2008
71.	J. L. F.Chacon, “Fault Detection in Rotating Machinery using Acoustic Emission,” Ph.D. Thesis, Brunel University London, 2015
72.	D. Mba and R. B. K. N. Rao, “Development of Acoustic Emission Technology for Condition Monitoring and Diagnosis of Rotating Machines; Bearings, Pumps, Gearboxes, Engines and Rotating Structures,” The Shock and Vibration Digest, Vol. 38, No. 1, pp. 3-16, 2006
73.	J. L. F.Chacon, E. A. Andicoberry, V. Kappatos, G. Asfis, T. H. Gan, and W. Balachandran, “Shaft Angular Misalignment Detection using Acoustic Emission,”Applied Acoustics, Vol. 85, pp. 12-22, 2014
74.	R. Li and D. He, “Rotational Machine Health Monitoring and Fault Detection using EMD-based Acoustic Emission Feature Quantification,” IEEE Transactions on Instrumentation and Measurement, Vol. 61, No. 4, pp. 990-1001, 2012
75.	K. V. Sivarao, G. Diwakar,M. R. S.Satyanarayana, “Determination Of Misalignment using Motor Current Signature Analysis in Rotating Machine,” IJERT, Vol. 1, No. 8, pp. 1-11, 2012
76.	C. Verucchia, J. Bossiob, G. Bossiob,G. Acosta, “Misalignment Detection in Induction Motors with Flexible Coupling by Means of Estimated Torque Analysis and MCSA,”Mechanical Systems and Signal Processing, Vol. 80, pp. 570-581, 2016
77.	A. Bouzida, O. Touhami, R. Ibtiouen, A. Belouchrani, M. Fadel,A. Rezzoug, “Fault Diagnosis in Industrial Induction Machines Through Discrete Wavelet Transform,” IEEE Transactions on Industrial Electronics, Vol. 58, No. 9, pp. 4385-4395, 2011
78.	I. Ahmed, M. Ahmed, K. Imran, M. S. Khan, T. Akram,M. Jawad, “Spectral Analysis of Misalignment in Machines using Sideband Components of Broken Rotor Bar, Shorted Turns and Eccentricity,” International Journal of Electrical and Computer Sciences IJECS-IJENS, Vol. 10, No. 6, pp. 85-93, 2010
79.	J. M. Bossio, G. R. Bossio,C. H.De Angelo, “Angular Misalignment in Induction Motors with Flexible Coupling,” inProceedings of 35th Annual Conference of IEEE Industrial Electronics, pp. 1033-1038, 2009
80.	R. R.Obaid and T. G. Habetler, “Effect of Load on Detecting Mechanical Faults in Small Induction Motors,” inProceedings of 4th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics, and Drives, pp. 307-311, 2003
81.	R. R. Obaid, T. G. Habetler,R. M. Tallam, “Detecting Load Unbalance and Shaft Misalignment using Stator Current in Inverter-Driven Induction Motors,” inProceedings of IEEE International Electric Machines and Drives Conference 3, pp. 1454-1458, 2003
82.	R. R.Obaid and T. G. Habetler, “Effect of Load on Detecting Mechanical Faults in Small Induction Motors,” inProceedings of Symposium on Diagnostics for Electric Machines, Power Electronics and Driver, pp. 307-311, 2003
83.	R. R.Obaid and T. G. Habetler, “Current-based Algorithm for Mechanical Fault Detection in Induction Motors with Arbitrary Load Conditions,” inProceedings of 38th IAS Annual Meeting on Conference Record of the Industry Applications Conference 2, pp. 1347-1351, 2003
84.	A. Simm, Q. Wang, S. Huang,W. Zhao, “Laser-based Measurement for the Monitoring of Shaft Misalignment,”Measurement, Vol. 87, pp. 104-116, 2016
85.	O. Mankowski and Q. Wang, “Real-Time Monitoring of Wind Turbine Generator Shaft Alignment using Laser Measurement,” inProceedings of 2nd International Through-life Engineering Services Conference 11, pp. 291-295, 2013
86.	A. R.Mohanty and S. Fatima, “Shaft Misalignment Detection by Thermal Imaging of Support Bearings,”IFAC(International Federation of Automatic Control), pp. 554-559, 2015
87.	S. Taib, M. S. Jadin,S. Kabir, “Thermal Imaging for Enhancing Inspection Reliability: Detection and Characterization,” Intech Open, pp. 209-236, 2012
88.	F. Al Thobiani, V. T. Tran,T. Tinga, “An Approach to Fault Diagnosis of Rotating Machinery using the Second-Order Statistical Features of Thermal Images and Simplified Fuzzy,”ARTMAP, Engineering, Vol. 9, pp. 524-539, 2017
89.	S. Fatima, A. R. Mohanty,V. N. A.Naikan, “A Misalignment Detection Methodology by Measuring Rate of Temperature Rise of Shaft Coupling using Thermal Imaging,” in Proc IMechE Part O: J Risk and Reliability, Vol. 229, No. 3, pp. 209-219, 2015
90.	O. Tonks and Q. Wang, “The Detection of Wind Turbine Shaft Misalignment using Temperature Monitoring,”CIRP Journal of Manufacturing Science and Technology, Vol. 17, pp. 71-79, 2017
91.	F. Jeffali, B. E. L.Kihel, A. Nougaoui, and F. Delaunois, “Monitoring and Diagnostic Misalignment of Asynchronous Machines by Infrared Thermography,” Journal of Materials and Environmental Sciences, Vol. 6, No. 4, pp. 1192-1199, 2015
92.	P. Gupta and O. P. Gandhi, “Coast-Down Time Monitoring for Defect Detection in Rotating Equipment,” International Journal of Performability Engineering, Vol. 10, No. 2, pp. 197-210, 2014
93.	G. R. Rameshkumar, B. V. A.Rao, and K. P. Ramachandran, “Prediction of Coast Down Time for Mechanical Faults in Rotating Machinery using Artificial Neural Networks,” International Journal of Mechanical and Mechatronics Engineering, Vol. 5, No. 3, pp. 559-566, 2011
94.	A. Harees and S. Harees, “CDT Analysis as a Tool for Evaluating Bearing Lubrication and Mechanical Conditions,” International Journal of Innovative Studies in Sciences and Engineering Technology, Vol. 2, No. 12, pp. 2455-4863, 2016
95.	A. S.Al-khuiatari and G. R. Rameshkumar, “Application of Artificial Neural Networks in Prediction of Mechanical Faults using Coast down Time,” International Journal of Emerging Technology and Advanced Engineering, Vol. 3, No. 7, 2013
96.	P. Arumugam, S. Swarnamani,B. S. Prabhu, “Effects of Journal Misalignment on the Performance Characteristics of Three-Lobe Bearings,”Wear, Vol. 206, pp. 122-129, 1997
97.	K. P. Ramachandran, M. Mahadevappa, M. K. Ravishankar,A. Ramakrishna, “An Approach to Machine Misalignment Studies using Vibration, Orbit, and Coast Down Phenomena,” inProceedings of the International Conference on Advances in Mechanical and Industrial Engineering, pp. 251-258, 1997

[1]	Yassine Eddouh, Abdelmajid Daya, Rabie Elotmani, and Abdelhamid Touache. Imperfect Maintenance Model for Optimizing Air Compressor Availability [J]. Int J Performability Eng, 2023, 19(4): 263-272.
[2]	Leila M. Bogdanova, Sergey Ya. Nagibin, and Alexander S. Chemakin. Analysis of the Criteria for Assessing the Forecast Quality of Industrial Safety Indicators of Enterprises [J]. Int J Performability Eng, 2021, 17(6): 519-527.
[3]	Apoorva Khairnar, Abhishek Patange, Sujit Pardeshi, and R. Jegadeeshwaran. Supervision of Carbide Tool Condition by Training of Vibration-based Statistical Model using Boosted Trees Ensemble [J]. Int J Performability Eng, 2021, 17(2): 229-240.
[4]	Shuo Meng, Jianshe Kang, Kuo Chi, and Xupeng Die. Intelligent Fault Diagnosis of Gearbox based on Multiple Synchrosqueezing S-Transform and Convolutional Neural Networks [J]. Int J Performability Eng, 2020, 16(4): 528-536.
[5]	Siyu Li, Shaoluo Huang, Yangyang Zhang, Lijun Cao, and Weiyi Wu. Deep Learning in Fault Diagnosis of Complex Mechanical Equipment [J]. Int J Performability Eng, 2020, 16(10): 1548-1555.
[6]	Sibo Li, Yongqin Zhou, Ran Li, and Xu Zhao. Online Lithium Battery Fault Diagnosis based on Least Square Support Vector Machine Optimized by Ant Lion Algorithm [J]. Int J Performability Eng, 2020, 16(10): 1637-1645.
[7]	Yunjie Li, Yanyu Wang, Jianchuan Zhang, Detai Zhou, and Dan Mo. HIMM Fault Diagnosis based on KPI [J]. Int J Performability Eng, 2019, 15(9): 2476-2483.
[8]	Yu Wang, Shuai Yang, and René Vinicio Sánchez. Wind Turbine Gearbox Fault Diagnosis using SAE-BP Transfer Neural Network [J]. Int J Performability Eng, 2019, 15(9): 2504-2514.
[9]	Junxi Bi, Chenglong Zheng, Hongzhong Huang, Xiaojuan Song, and Jinfeng Li. Fault Diagnosis of Wind Turbine Blades based on Wavelet Theory and Neural Network [J]. Int J Performability Eng, 2019, 15(7): 1895-1904.
[10]	Shijie Deng, Liwei Tang, Xujun Su, and Jinli Che. Fault Diagnosis Technology of Plunger Pump based on EMMD-Teager [J]. Int J Performability Eng, 2019, 15(7): 1912-1919.
[11]	Yuguo Xu, Shixin Zhang, Yong Li, and Jiawang Liu. Ontology-based Fault Diagnosis and Maintenance Process Generation of Electromechanical System [J]. Int J Performability Eng, 2019, 15(2): 454-463.
[12]	Xiang Duan, Jianyu Long, Chuan Li, Diego Cabrera, and Shaohui Zhang. Intelligent Fault Diagnosis of 3D Printers based on Reservoir Computing [J]. Int J Performability Eng, 2019, 15(12): 3171-3178.
[13]	Xiaoyan Li, Jianwen Guo, Xuejun Jia, Shaohui Zhang, and Zhiyuan Liu. Intelligent Fault Diagnosis of Delta 3D Printers using Attitude Sensors based on Extreme Learning Machines [J]. Int J Performability Eng, 2019, 15(12): 3196-3208.
[14]	Jianyu Long, Ying Hong, Shaohui Zhang, Diego Cabrera, and Jingjing Zhong. Improving Extreme Learning Machine by a Level-based Learning Swarm Optimizer and its Application to Fault Diagnosis of 3D Printers [J]. Int J Performability Eng, 2019, 15(11): 2972-2981.
[15]	Zhiwu Shang, Xia Liu, Xiangxiang Liao, Rui Geng, Maosheng Gao, and Jintian Yun. Rolling Bearing Fault Diagnosis Methodbased on EEMD and GBDBN [J]. Int J Performability Eng, 2019, 15(1): 230-240.