[1] R Y Zhong, X Xu, E Klotz, et al. Intelligent manufacturing in the context of Industry 4.0: A review. Engineering, 2017, 3(5): 616-630.
[2] H R Cao, X W Zhang, X F Chen. The concept and progress of intelligent spindles: A review. International Journal of Machine Tools and Manufacture, 2017, 112: 21-52.
[3] P P Ma, J Y Zhai, H Zhang, et al. Multi-body dynamic simulation and vibration transmission characteristics of dual-rotor system for aeroengine with rubbing coupling faults. Journal of Vibroengineering, 2019, 21(7): 1875-1887.
[4] J Hong, M L Xu, D Y Zhang, et al. Safety design method of fan rotor system in aeroengine due to extreme loadings. Proceeding of the First International Conference on Reliability Systems Engineering ICRSE, Beijing, China, October 21-23, 2015.
[5] P C Yu, D Y Zhang, Y H Ma. Dynamic modeling and vibration characteristics analysis of the aero-engine dual-rotor system with Fan blade out. Mechanical Systems And Signal Processing, 2018, 106: 158-175.
[6] Institute for Strategic Research in Advanced Manufacturing. Advanced manufacturing technology in China- a roadmap to 2050. Beijing: Science Press, 2015. (in Chinese)
[7] J J Gao. A study of the fault Self-recovery regulation for process equipment. Proceedings of International Conference on Intelligent Maintenance Systems, Xi'an, China, October 25-27, 2003: 781.
[8] J J Gao. Artificial Self-recovery and machinery self-recovery regulation system. Journal of Mechanical Engineering, 2018, 54(8): 83-94. (in Chinese)
[9] Consulting Project Group of Chinese Academy of Engineering. Research reports on engineering science and technology and development strategy — Proposal of equipment failure self-recovery engineering and its application in China. Beijing: Chinese Academy of Engineering, 2006. (in Chinese)
[10] J J Gao. Mechanical fault diagnosis and self-recovery. Beijing: Higher Education Press, 2012. (in Chinese)
[11] Corporation LORD. Real-Time Balancing Solutions for the Aerospace & Defense Industry. 2011[2020-11-11]. https://www.lord.com/china/sites/china/files/PB6056_PropellerBalancingBrochure.pdf.
[12] Corporation Marposs. Active Control of Vibrations on Grinders. 2005[2020-11-11]. https://www.marposs.com/chi/download.
[13] H W Fan, M Q Jing, R C Wang, et al. New electromagnetic ring balancer for active imbalance compensation of rotating machinery. Journal of Sound and Vibration, 2014, 333(17): 3837-3858.
[14] X Pan, H Q Wu, J J Gao. Rotating machinery targeting self-recovery regulation system for imbalance vibration fault with liquid-transfer active balancing Device. Journal of Mechanical Engineering, 2015, 51(1): 146-152.
[15] X L Qiao, C S Zhu. The active unbalanced vibration compensation of the flexible switched reluctance motorized spindle. Journal of Vibration and Control, 2014, 20(13): 1934-1945.
[16] Y S Chen, H B Zhang. Review and prospect on the research of dynamics of complete aero-engine systems. Acta Aeronautica et Astronautica Sinica, 2011, 32(8): 1371-1391.
[17] J J Gao, B Ma, Z N Jiang. Research on fault self-recovery engineering. Journal of Dalian University of Technology, 2006, 46(3): 153-161.
[18] L F Chen, W M Wang, J J Gao. Summary on the development of auto-balancing technology of aero-engine. Journal of Aerospace Power, 2019, 34(7): 1530-1541.
[19] E Wilson, K Hale, M Strohmeyer. V-22 rotor track and balance on-board and ground station functionality and field experience. 2011 IEEE Aerospace Conference, AERO 2011, Big Sky, MT, March 5-12, 2011.
[20] W Q Deng, G Tang, D P Gao. Research summary of rotor dynamic characteristics and dynamic balance. Gas Turbine Experiment and Research, 2008, 21(2): 57-62.
[21] B Y Chen. Development of aero engine balancing technology. Journal of Propulsion Technology, 1998, 19(4): 7-10.
[22] P Bart, H Wim, D Jan, et al. Modern solutions for ground vibration testing of large aircraft. Sound and Vibration, 2009, 43(1): 8-15.
[23] J L White, M A Heidari, M H Travis. Experience in rotor balancing of large commercial jet engines. 13th International Modal Analysis Conference, Nashville, USA, February 13-19, 1995.
[24] B Rebbechi, P R Marsden, S B J Church. C-130J in-flight propeller balancing. In 7th DSTO International Conference on Health & Usage Monitoring (Australian International Aerospace Congress), 2011.
[25] Q F Xu, S X Lu, W Y Jia, et al. Imbalanced fault diagnosis of rotating machinery via multi-domain feature extraction and cost-sensitive learning. Journal of Intelligent Manufacturing, 2019: 1-15.
[26] A S Sait, Y I Sharaf-Eldeen. A review of gearbox condition monitoring based on vibration analysis techniques diagnostics and prognostics. Rotating Machinery, Structural Health Monitoring, Shock and Vibration, 2011, 5: 307-324.
[27] D Goyal, B S Pabla. The vibration monitoring methods and signal processing techniques for structural health monitoring: A review. Archives of Computational Methods in Engineering, 2016, 23(4): 585-594.
[28] A Kumar, R Kumar. Role of signal processing, modeling and decision making in the diagnosis of rolling element bearing defect: A review. Journal of Nondestructive Evaluation, 2019, 38(1): 5.
[29] C Malla, I Panigrahi. Review of condition monitoring of rolling element bearing using vibration analysis and other techniques. Journal of Vibration Engineering & Technologies, 2019, 7(4): 407-414.
[30] L Deng, R Zhao. Fault feature extraction of a rotor system based on local mean decomposition and Teager energy kurtosis. Journal of Mechanical Science and Technology, 2014, 28(4): 1161-1169.
[31] F D Sanches, R Pederiva. Simultaneous identification of unbalance and shaft bow in a two-disk rotor based on correlation analysis and the SEREP model order reduction method. Journal of Sound & Vibration, 2018, 433: 230-247.
[32] D He, X F Wang, S Li, et al. Identification of multiple faults in rotating machinery based on minimum entropy deconvolution combined with spectral kurtosis. Mechanical Systems and Signal Processing, 2016, 81: 235-249.
[33] D Ibarra-Zarate, O Tamayo-Pazos, A Vallejo-Guevara. Bearing fault diagnosis in rotating machinery based on cepstrum pre-whitening of vibration and acoustic emission. The International Journal of Advanced Manufacturing Technology, 2019, 104(9-12): 4155-4168.
[34] G Chen. Characteristics analysis of blade-casing rubbing based on casing vibration acceleration. Journal of Mechanical Science and Technology, 2015, 29(4): 1513-1526.
[35] G Chen, Y Q Liu, G Y Jiang, et al. A novel method for identifying rotor-stator rubbing positions using the cepstrum analysis technique. Journal of Mechanical Science and Technology, 2014, 28(9): 3537-3544.
[36] H Li, Y P Zhang, H Q Zheng. Gear fault detection and diagnosis under speed-up condition based on order cepstrum and radial basis function neural network. Journal of Mechanical Science and Technology, 2009, 23(10): 2780-2789.
[37] B Liang, S D Iwnicki, Y Zhao. Application of power spectrum, cepstrum, higher order spectrum and neural network analyses for induction motor fault diagnosis. Mechanical Systems and Signal Processing, 2003, 39(1-2): 342-360.
[38] J Urbanek, T Barszcz, R Zimroz, et al. Application of averaged instantaneous power spectrum for diagnostics of machinery operating under non-stationary operational conditions. Measurement, 2012, 45(7): 1782-1791.
[39] I Yesilyurt. Fault detection and location in gears by the smoothed instantaneous power spectrum distribution. NDT and E International, 2003, 36(7): 535-542.
[40] T H Patel, A K Darpe. Application of full spectrum analysis for rotor fault diagnosis. IUTAM Symposium on Emerging Trends in Rotor Dynamics, 2011, 1011: 535-545.
[41] Y G Lei, J Lin, Z J He, et al. A review on empirical mode decomposition in fault diagnosis of rotating machinery. Mechanical Systems and Signal Processing, 2013, 35(1-2): 108-126.
[42] V H Nguyen, J S Cheng, Y Yu, et al. An architecture of deep learning network based on ensemble empirical mode decomposition in precise identification of bearing vibration signal. Journal of Mechanical Science and Technology, 2019, 33(1): 41-50.
[43] H Wang, J J Gao, Z N Jiang, et al. Rotating machinery fault diagnosis based on EEMD time-frequency energy and SOM neural network. Arabian Journal for Science and Engineering, 2014, 39(6): 5207-5217.
[44] Z L Xie, B L Shang, R X Zhou. Application of EMD-ICA and demodulation to early failure diagnosis of rotor systems. Proceedings of the First Symposium on Aviation Maintenance and Management, 2014, 296: 361-372.
[45] Y He, D C Pi. Anomaly detection algorithm for helicopter rotor based on STFT and SVDD. Cloud Computing and Security, ICCCS 2016, PT Ⅱ, 2016, 10040: 383-393.
[46] Y Jin, Z Y Hao, X Zheng. Comparison of different techniques for time-frequency analysis of internal combustion engine vibration signals. Journal of Zhejiang University: Science A, 2011, 12(7): 519-531.
[47] N H Chandra, A S Sekhar. Fault detection in rotor bearing systems using time frequency techniques. Mechanical Systems and Signal Processing, 2016, 72: 105-133.
[48] B Li, C L Zhang, Z J He. HHT-based crack identification method for start-up rotor. Frontiers of Mechanical Engineering, 2012, 7(3): 300-304.
[49] S M Li, J R Wang, X L Li. Theoretical analysis of adaptive harmonic window and its application in frequency extraction of vibration signal. Journal of Central South University, 2018, 25(1): 241-250.
[50] X J Fu. Research on vibration of rotor by application of the improved harmonic wavelet. Analog Integrated Circuits and Signal Processing, 2009, 59(2): 201-205.
[51] V Muralidharan, V Sugumaran. Feature extraction using wavelets and classification through decision tree algorithm for fault diagnosis of mono-block centrifugal pump. Measurement, 2013, 46(1): 353-359.
[52] F Al-Badour, M Sunar, L Cheded. Vibration analysis of rotating machinery using time-frequency analysis and wavelet techniques. Mechanical Systems and Signal Processing, 2011, 25(6): 2083-2101.
[53] Q Hu, Z J He, Z S Zhang, et al. Fault diagnosis of rotating machinery based on improved wavelet package transform and SVMs ensemble. Mechanical Systems and Signal Processing, 2007, 21(2): 688-705.
[54] W T Shan, X A Chen, Y He, et al. A novel experimental research on vibration characteristics of the running high-speed motorized spindles. Journal of Mechanical Science and Technology, 2013, 27(8): 2245-2252.
[55] T H G Lobato, R R da Silva, E S da Costa, et al. An integrated approach to rotating machinery fault diagnosis using, EEMD, SVM, and augmented data. Journal of Vibrational Engineering and Technologies, 2020, 8: 403-408.
[56] X Hu, J Vian, J R Slepski, et al. Vibration analysis via neural network inverse models to determine aircraft engine unbalance condition. Neural Networks. International Joint Conference on Neural Networks, Portland, USA, July 20-24, 2003: 3001-3006.
[57] X X Zhu, D N Hou, P Zhou, et al. Rotor fault diagnosis using a convolutional neural network with symmetrized dot pattern images. Measurement, 2019, 138: 526-535.
[58] J H Yan, Y Y Hu, C Z Guo, Rotor unbalance fault diagnosis using DBN based on multi-source heterogeneous information fusion. Procedia Manufacturing, 2019, 35: 1184-1189.
[59] S Y Shao, W J Sun, R Q Yan, et al. A deep learning approach for fault diagnosis of induction motors in manufacturing. Chinese Journal of Mechanical Engineering, 2017, 30(6): 1347-1356.
[60] J T Cheng, L Wang, X Yan. Cuckoo search algorithm with memory and the vibrant fault diagnosis for hydroelectric generating unit. Engineering with Computers, 2019, 35(2): 687-702.
[61] G Li, G L McDonald, Q Zhao. Sinusoidal synthesis based adaptive tracking for rotating machinery fault detection. Mechanical Systems and Signal Processing, 2017, 83: 356-370.
[62] L Lu, J H Yan, C W De Silva. Dominant feature selection for the fault diagnosis of rotary machines using modified genetic algorithm and empirical mode decomposition. Journal of Sound and Vibration, 2015, 344: 464-483.
[63] H X Deng, Y F Diao, W Wu, et al. A high-speed D-CART online fault diagnosis algorithm for rotor systems. Applied Intelligence, 2020, 50(1): 29-41.
[64] Y A Khulief, M A Mohiuddin, M El-Gebeily. A new method for field-balancing of high-speed flexible rotors without trial weights. International Journal of Rotating Machinery, 2014: 603241.
[65] Y A Khulief, W Oke, M A Mohiuddin. Modally tuned influence coefficients for low-speed balancing of flexible rotors. Journal of Vibration and Acoustics, Transactions of the ASME, 2014, 136(2): 024501.
[66] C H Li, Z L Han, C Du, et al. Numerical study on critical speed modeling of ultra-high speed grinder spindle. Advances in Information Technology and Education, 2011, 201: 202-209.
[67] M B Deepthikumar, A S Sekhar, M R Srikanthan. Modal balancing of flexible rotors with bow and distributed unbalance. Journal of Sound and Vibration, 2013, 332(24): 6216-6233.
[68] M S Darlow. Balancing of high-speed machinery: Theory, methods and experimental results. Mechanical Systems and Signal Processing, 1987, 1(1): 105-134.
[69] G F Bin, X J Li, Y P Shen, et al. Development of whole-machine high speed balance approach for turbomachinery shaft system with N?+?1 supports. Measurement, 2018, 122: 368-379.
[70] Y Kang, T W Lin, Y J Chang, et al. Optimal balancing of flexible rotors by minimizing the condition number of influence coefficients. Mechanism and Machine Theory, 2008, 43(7): 891-908.
[71] T P Goodman. A least-squares method for computing balance corrections. Journal of Engineering for Industry, 1964, 86(3): 273-275.
[72] W P Lei, J Han, H Chen, et al. The modified balance method based on precession decomposition. 2011 IEEE International Conference on Computer Science and Automation Engineering, Shanghai, China, June 10-12, 2011: 632-636.
[73] G Ranjan, R Tiwari. Application of active magnetic bearings for in situ flexible rotor residual balancing using a novel generalized influence coefficient method. Inverse Problems in Science and Engineering, 2019, 27(7): 943-968.
[74] F Fujisawa, K Shiohato, K Sato, et al. Experimental investigation of multi-span rotor balancing using least squares method. Journal of Mechanical Design, 1980, 102(3): 589-596.
[75] Y Kang, C P Liu, G J Sheen. A modified influence coefficient method for balancing unsymmetrical rotor-bearing systems. Journal of Sound and Vibration, 1996, 194(2): 199-218.
[76] J D Moon, B S Kim, S H Lee. Development of the active balancing device for high-speed spindle system using influence coefficients. International Journal of Machine Tools and Manufacture, 2006, 46(9): 978-987.
[77] C D Untaroiu, P E Allaire, W C Foiles. Balancing of flexible rotors using convex optimization techniques: Optimum Min-Max LMI influence coefficient balancing. Journal of Vibration and Acoustics, Transactions of the ASME, 2008, 130(2): 021006-021010.
[78] X Xu, P P Fan. Rigid rotor dynamic balancing by two-plane correction with the influence coefficient method. Machine Design and Manufacturing Engineering Ⅱ, PTS 1 and 2, 2013, 365-366: 211-215.
[79] D J Han. Generalized modal balancing for non-isotropic rotor systems. Mechanical Systems and Signal Processing, 2007, 21(5): 2137-2160.
[80] G F Bin, Y Huang, S P Guo, et al. Investigation of induced unbalance magnitude on dynamic characteristics of high-speed turbocharger with floating ring bearings. Chinese Journal of Mechanical Engineering, 2018, 31: 88, https://doi.org/https://doi.org/10.1186/s10033-018-0287-5.
[81] C Quartarone, J Beqari, J G Detoni, et al. Balancing of turbomolecular pumps: Modal balancing approach and experimental results. Mechanisms and Machine Science, 2019, 63: 119-128.
[82] G R Wen, X N Zhang, M Zhao. Application of partical swarm optimization algorithm in field holo-balancing. Life System Modeling and Intelligent Computing, 2010, 6328: 16-25.
[83] S Liu. A modified low-speed balancing method for flexible rotors based on holospectrum. Mechanical Systems and Signal Processing, 2006, 21(1): 348-364.
[84] S Liu, L S Qu. A new field balancing method of rotor systems based on holospectrum and genetic algorithm. Applied Soft Computing Journal, 2008, 8(1): 446-455.
[85] Y M Ram, J E Mottershead. Multiple-input active vibration control by partial pole placement using the method of receptances. Mechanical Systems and Signal Processing, 2013, 40(2): 727-735.
[86] R Ariyatanapol, Y P Xiong, H J Ouyang. Partial pole assignment with time delays for asymmetric systems. Acta Mechanica, 2018, 229(6): 2619-2629.
[87] H Gao, L X Xu. Real-time feed-forward force compensation for active magnetic bearings system based on H∞ controller. Chinese Journal of Mechanical Engineering, 2011, 24(1): 58-66.
[88] C Liu, D Ye, K Shi, et al. Robust high-precision attitude control for flexible spacecraft with improved mixed H2/H∞ control strategy under poles assignment constraint. Acta Astronautica, 2017, 136(1): 166-175.
[89] J H Fan, Y M Zhang, Z Q Zheng. Adaptive observer-based integrated fault diagnosis and fault-tolerant control systems against actuator faults and saturation. Journal of Dynamic Systems, Measurement and Control, 2013, 135(4): 0022-0434.
[90] C Peng, J X He, M T Zhu, et al. Optimal synchronous vibration control for magnetically suspended centrifugal compressor, Mechanical Systems and Signal Processing, 2019, 132: 776-789.
[91] G S Tombul, S P Banks. Nonlinear optimal control of rotating flexible shaft in active magnetic bearings. Science China Technological Sciences, 2011, 54(5): 1084-1094.
[92] A Rosyid, M ElMadany, M Alata. Optimal control of reduced-order finite element models of rotor-bearing-support systems. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2015, 37(5): 1485-1497.
[93] L Zhang, K Liu. Riccati difference equation in optimal control for magnetic bearings. Science China Technological Sciences, 2012, 55(8): 2107-2114.
[94] L H Yang, Y H Sun, L Yu. Active control of unbalance response of rotor systems supported by tilting-pad gas bearings. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 2012, 226(2): 87-98.
[95] V N Carvalho, B F R Rende, A D G Silva, et al. Robust balancing approach for rotating machines based on fuzzy logic. Journal of Vibration and Acoustics, 2018, 140(5): 051018.
[96] J Xu, Y Zhao, Z Y Jia, et al. Rotor dynamic balancing control method based on fuzzy auto-tuning single neuron PID. IEICE Electronics Express, 2017, 14(10): 1349-2543.
[97] W A Oke, M A Abido, T B Asafa. Balancing of flexible rotors based on evolutionary algorithms. Mechanics & Industry, 2015, 16(4): 406.
[98] X Yang, C Zhang. Optimization for discrete balance weights based on hybrid genetic algorithm. 2011 IEEE International Conference on Computer Science and Automation Engineering, Shanghai, China, June 10-12, 2011, 2: 76-79.
[99] D Yao, J Wang, Y Liu. Enhancing working performance of active magnetic bearings using improved fuzzy control and Kalman-LMS filter. Journal of Intelligent & Fuzzy Systems, 2015, 29(4): 1343-1353.
[100] M L Adams. Rotor balancing and unbalance-caused vibration. Handbook of Noise and Vibration Control, 2008, 57(1): 753-760.
[101] X B Xu, J C Fang, H T Li, et al. Active suppression of imbalance vibration in the magnetically suspended control moment gyro. Journal of Vibration and Control, 2015, 21(5): 989-1003.
[102] S Kwang-Keun. Adaptive control of active balancing systems for speed-varying rotating machinery. University of Michigan, 2001.
[103] S H Zhang, Z M Zhang, L W Yan. Recent researches and patents on dynamic balancing methods and devices for rotor system. Recent Patents on Mechanical Engineering, 2016, 9(3): 222-229.
[104] E N Pashkov, N V Martyushev, P G Yurovsky. Stationary rotation of the partially liquid-filled unbalanced rotor under external friction force action. High Technology: Research and Applications, 2014, 1040(1): 903-906.
[105] U S Leonardo, L P Marcelo. Liquid self-balancing device effects on flexible rotor stability. Shock and Vibration, 2013, 20(1): 109-121.
[106] D Ilona, T Viktor, P Kęstutis, et al. Operation of passive fluid self-balancing device at resonance transition regime. Mechanika, 2018, 24(6): 805-810.
[107] P Chao, C W Chiu, K T Shih. A novel low-torque ball re-positioning scheme based on a sliding-mode ball observer for an automatic balancer system. Shock and Vibration, 2008, 15(2): 101-126.
[108] H DeSmidt. Automatic balancing of bladed-disk/shaft system via passive auto-balancer devices. 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference 16th AIAA/ASME/AHS Adaptive Structures Conference, Schaumburg, USA, April 7-10, 2008.
[109] V Goncharov, G Filimonikhin, K Dumenko, et al. Studying the peculiarities of balancing of flexible double-support rotors by two passive automatic balancers placed near supports. Eastern-European Journal of Enterprise Technologies, 2016, 4(7): 4-9.
[110] R Shibuya, R Tasaki, K Terashima, Modeling and analysis on stream-tube of pouring flow with a pair of multi-pendulum in self-transfer-type automatic pouring robot. 71st World Foundry Congress: Advanced Sustainable Foundry, Bilbao, Spain, May 18-22, 2014.http://www.researchgate.net/publication/289029669_Modeling_and_analysis_on_stream-tube_of_pouring_flow_with_a_pair_of_multi-pendulum_in_self-transfer-type_automatic_pouring_robot
[111] Y R Su, L D He, W Feng. A study of the active balancing technology for the far end optimization of a cantilever rotor. Journal of Engineering for Thermal Energy and Power, 2008, 23(4): 369-372.
[112] Y R Su, L D He, Z Wang, et al. Study on dual-plane active hydraulic balancing technology for single-disk rigid rotor system. Proceedings of the CSEE, 2009, 29(35): 119-124.
[113] Y Zhang, X S Mei. Study of online balancing control technique for high- speed spindles. Engineering Sciences, 2013, 15(1): 87-92.
[114] X L Yun, X S Mei, G D Jiang, et al. Investigation on a no trial weight spray online dynamic balancer. Shock and Vibration, 2018, 2018: 1-15.
[115] S J Jørren, P Martin. A centrifugal fiberising spinner unit and a method of automatically balancing such unit: DK, 2016008797, 2016-01-21, https://worldwide.espacenet.com/publicationDetails/originalDocument?FT=D&date=20160120&DB=EPODOC&local=en_EP&CC=EP&NR=2975006A1&KC=A1&ND=4.
[116] S Z He. Study of liquid release auto-balancing head. Journal of Zhejiang University (Engineering Science), 2001, 35(4): 418-422.
[117] J J Gao, P Zhang. Simulative study of automatic balancing of grinding wheel using a continuously dripping liquid- injection balancing head. WCICA 06, The Sixth World Congress on Intelligent Control and Automation. Piscataway, Dalian, China, June 21-23, 2006: 8002-8005.
[118] Y Li, W M Wang, L Q Huang, et al. A rotor auto-balance device with continuously injecting and draining liquid based on peristaltic pumps. Journal of Vibration and Shock, 2011, 30(4): 38-41.
[119] R Rumin, M Bergander, J Cieslik, et al. Extended active vibration control for wind turbines. 2017 XⅢth International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH), Suzhou, China, October 25-27, 2017.
[120] X N Zhang, X Liu, H Zhao. New active online balancing method for grinding wheel using liquid injection and free dripping. Journal of Vibration and Acoustics-Transactions of the ASME, 2018, 140(3): 031001.
[121] J Steere, T Lewandowski. Balanced rotary saw assembly and a method of balancing the same: US, 4537177, 1985-08-27. https://www3.drugfuture.com/uspat/download/US4537177.pdf.
[122] J C Coyne, R T LaGrotta, et al. Liquid-chamber apparatus for active dynamic balancing of rotating machinery: US, 5490436, 1996-02-13. http://www3.drugfuture.com/uspat/download/US5490436.pdf.
[123] K Nakamoto, S Mitsuhashi, H Nakatsuji, et al. Real-time balancing mechanism using magnetic fluid for a machine tool spindle (2nd Report)-Development of a machine tool spindle to verify real-time balancing mechanism. International Journal of the Japan Society of Precision Engineering, 2010, 76(11): 1271-1275.
[124] X N Zhang, X R Xia, Z Xiang, et al. An online active balancing method using magnetorheological effect of magnetic fluid. Journal of Vibration and Acoustics-Transactions of the ASME, 2019, 141(1): 011008.
[125] X Pan, H Q Wu, J J Gao, et al. New liquid transfer active balancing system using compressed air for grinding machine. Journal of Vibration and Acoustics-Transactions of the ASME, 2015, 137(1): 011014.
[126] X Pan, Z Xie, J Lu, et al. Novel liquid transfer active balancing system for hollow rotors of high-speed rotating machinery. Applied Sciences, 2019, 9(5): 833.
[127] Corporation Dittel. Balancing systems for grinding machines. Bologna: Marposs Group, 2012. https://www.dittel.com.
[128] J V Vegte, R T Lake. Balancing of rotating systems during operation. Journal of Sound and Vibration, 1978, 57(2): 225-235.
[129] Y D Kim, C W Lee. Determination of the optimal balancing head location on flexible rotors using a structural dynamics modification algorithm. Proceedings of the Institution of Mechanical Engineers, Part C: Mechanical Engineering Science, 1985, 199(1): 19-25.
[130] Y Li, Y P Lu. Experimental study on vibration control of a PMDF electric balancing head. Journal of Vibration Engineering, 2000, 13(2): 302-306.
[131] B Hredzak, G X Guo. New electromechanical balancing device for active imbalance compensation. Journal of Sound and Vibration, 2006, 294: 737-751.
[132] Corporation Schmitt. Operation and specification manual for the SBS dynamic balance system-Model 4500 series Control Unit. Portland: Accretech SBS Inc, 2020. https://accretechsbs.com/wpcontent/.uploads/MAN-SB-4500-Mechanic-Balancer-EN.pdf.
[133] Q H Esteban. Method for balancing a propulsive system having non-hull contra-rotating propellers: US, 20120328439, 2012-12-27. http://www3.drugfuture.com/uspat/download/US20120328439.pdf.
[134] Y B Zhang, N Mo, Y Zhou, et al. Unbalance compensation and automatic balance of active magnetic bearing rotor system by using iterative learning control. IEEE Access, 2019, 7: 122613-122625.
[135] W M Wang, J J Gao, L Q Huang, et al. Experimental investigation on vibration control of rotor-bearing system with active magnetic exciter. Chinese Journal of Mechanical Engineering, 2011, 24(6): 1013-1021.
[136] H Gao, L X Xu, Y L Zhu. Unbalance vibratory displacement compensation for active magnetic bearings. Chinese Journal of Mechanical Engineering, 2013, 26(1): 95-103.
[137] M Hutterer, G Kalteis, M Schrodl. Redundant unbalance compensation of an active magnetic bearing system. Mechanical Systems and Signal Processing, 2017, 94: 267-278.
[138] S Y Yoon, L Di, Z L Lin. Unbalance compensation for AMB systems with input delay: An output regulation approach. Control Engineering Practice, 2016, 46: 166-175.
[139] S K Wan, X H Li, W J Su, et al. Active damping of milling chatter vibration via a novel spindle system with an integrated electromagnetic actuator. Precision Engineering, 2019, 57: 203-210.
[140] Company Hofmann. Active Balancing. Pfungstadt: Hofmann Corporation, 2018. https://www.hofmann-balancing.com/products/active-balancing-systems/ring-balancer-ab-9000.html.
[141] S W Dyer, J Ni. Adaptive influence coefficient control of single- plane active balancing systems for rotating machinery. Journal of Manufacturing Science and Engineering, 2001, 123 (3): 291-298.
[142] K K Shin, J Ni. Adaptive control of multi-plane active balancing systems for speed-varying rotors. Journal of Dynamic Systems, Measurement and Control, 2003, 125(9): 372-381.
[143] Y R Su, L D He. Study on online elimination of sudden unbalance-induced vibration using active balancing technology. High Technology Letters, 2010, 16(2): 209-214.
[144] L F Chen, X Cao, J J Gao. A study on electromagnetic driven bi-disc compensator for rotor auto-balancing and its movement control. WSEAS Transactions on Systems and Control, 2010, 5(5): 333-342.
[145] H W Fan, J J Zhi, B J Shi, et al. Adaptive rotor balancing algorithm and single-disk rotation test for electromagnetic balancer. Journal of Xi'an Jiaotong University, 2018, 52(8): 15-21, 29.
[146] X Pan, T X He, K Z Wei, et al. Performance analysis and experimental research of electromagnetic-ring active balancing actuator for hollow rotors of machine tool spindles. Applied Sciences, 2019, 9(4): 692.
