On-site high-speed balancing of flexible rotor-bearing system using virtual trial unbalances at slow run

Abstract An identification algorithm is developed to execute high-speed balancing of the flexible rotor system supported on the conventional bearings, while rotating the system below its critical speed. The system is integrated with Active Magnetic Bearings (AMBs) as a suppression actuator as well as an excitation actuator. The AMB suppresses the vibration of the system and allows to introduce virtual trial unbalances to identify the orientation and magnitude of the residual unbalances present in the system. An Advanced Influence Coefficient Method (AICM) is developed that utilizes the influence coefficients obtained at high speed and unbalances identified at the low speed to effectively estimate the balance masses required for the high-speed flexible rotor balancing. The influence coefficients are required to be obtained just the once, whereas the balance masses can be estimated periodically by identifying the unbalances at low speeds. After balancing, the system can easily cross its critical speeds with less vibration. The AMB also controls abrupt change in vibration amplitude due to any uncertain faults, while operating at high speeds. Additionally, the virtual trial unbalances as a magnetic force generated through AMB reduces the mechanical effort involved in the placing of physical trial unbalances in the rotor system. This method allows on-site condition monitoring of the system periodically to reduce the impairment of high-speed machinery.

[1]  Chun-Chieh Wang,et al.  An accuracy improvement for balancing crankshafts , 2003 .

[2]  Yun Zhang,et al.  A New Field Unbalance Estimation Method for Flexible Rotors , 2011 .

[3]  Conrad Gähler Rotor dynamic testing and control with active magnetic bearings , 1998 .

[4]  John J. Yu Relationship of Influence Coefficients Between Static-Couple and Multiplane Methods on Two-Plane Balancing , 2009 .

[5]  Shaoze Yan,et al.  A control method of the rotor re-levitation for different orbit responses during touchdowns in active magnetic bearings , 2018 .

[6]  Juan Hidalgo,et al.  PRACTICAL BALANCING OF FLEXIBLE ROTORS FOR POWER GENERATION , 2007 .

[7]  Stephan Rinderknecht,et al.  Vibration isolation for parameter-varying rotor systems using piezoelectric actuators and gain-scheduled control , 2017 .

[8]  Vikas Prasad,et al.  Identification of Speed-Dependent Active Magnetic Bearing Parameters and Rotor Balancing in High-Speed Rotor Systems , 2019, Journal of Dynamic Systems, Measurement, and Control.

[9]  Bangcheng Han,et al.  Optimization of Damping Compensation for a Flexible Rotor System With Active Magnetic Bearing Considering Gyroscopic Effect , 2015, IEEE/ASME Transactions on Mechatronics.

[10]  Mary Kasarda,et al.  Active magnetic bearing based force measurement using the multi-point technique , 2007 .

[11]  Manfred Schrödl,et al.  Selfsensing unbalance rejection and reduction of the gyroscopic effect for an active magnetic bearing system , 2015, 2015 10th Asian Control Conference (ASCC).

[12]  Bangcheng Han,et al.  Field Balancing of Magnetically Levitated Rotors without Trial Weights , 2013, Sensors.

[13]  Yeon-Pun Chang,et al.  Optimal balancing of flexible rotors by minimizing the condition number of influence coefficients , 2008 .

[14]  MB Deepthikumar,et al.  Balancing of flexible rotor with bow using transfer matrix method , 2014 .

[15]  Oh Sung Jun,et al.  Influence coefficients on rotor having thick shaft elements and resilient bearings , 2004 .

[16]  G. Silva-Navarro,et al.  Active Unbalance Control of Rotor Systems Using On‐Line Algebraic Identification Methods , 2013 .

[17]  Xiufeng Wang,et al.  SQP algorithms in balancing rotating machinery , 2007 .

[18]  Yehia A. Khulief,et al.  A New Method for Field-Balancing of High-Speed Flexible Rotors without Trial Weights , 2014 .

[19]  Lei Zhao,et al.  Identification of active magnetic bearing system with a flexible rotor , 2014 .

[20]  Andreas Binder,et al.  Modeling and digital control of an Active Magnetic Bearing System , 2007 .

[21]  Harold D. Nelson Steady Synchronous Response and Balancing of Rotor Systems with Residual Shaft Bow , 2002 .

[22]  Jian Yang,et al.  Dynamic Balancing of a Centrifuge: Application to a Dual-Rotor System with Very Little Speed Difference , 2004 .

[23]  Qingkai Han,et al.  Balancing method without trial weights for rotor systems based on similitude scale model , 2018 .

[24]  Yehia A. Khulief,et al.  Modally Tuned Influence Coefficients for Low-Speed Balancing of Flexible Rotors , 2014 .

[25]  F Dohnal,et al.  Current signature analysis for unbalance fault detection in a rotor supported by active magnetic bearings , 2014 .

[26]  Kuan-Yu Chen,et al.  Design of model-based unbalance compensator with fuzzy gain tuning mechanism for an active magnetic bearing system , 2011, Expert Syst. Appl..

[27]  Mary Kasarda,et al.  A Multi-Point Measurement Technique for the Enhancement of Force Measurement With Active Magnetic Bearings , 2001 .

[28]  Jarir Mahfoud,et al.  Vibration reduction of a single cylinder reciprocating compressor based on multi-stage balancing , 2013 .

[29]  Rajiv Tiwari,et al.  Identification of bearing dynamic parameters and unbalance states in a flexible rotor system fully levitated on active magnetic bearings , 2014 .

[30]  Jun Ni,et al.  Adaptive Influence Coefficient Control of Single-Plane Active Balancing Systems for Rotating Machinery , 1999, Manufacturing Science and Engineering.

[31]  Katia Lucchesi Cavalca,et al.  Characteristics of oil film nonlinearity in bearings and its effects in rotor balancing , 2019, Journal of Sound and Vibration.

[32]  Yuan Kang,et al.  A modified approach based on influence coefficient method for balancing crank-shafts , 2000 .

[33]  Paul E. Allaire,et al.  Balancing of Flexible Rotors Using Convex Optimization Techniques : Optimum Min-Max LMI Influence Coefficient Balancing , 2008 .

[34]  Régis Dufour,et al.  Influence of cylinder pressure on the balancing of a rotary compressor , 2006 .

[35]  Dara W. Childs,et al.  Identification of Rotordynamic Forces in a Flexible Rotor System Using Magnetic Bearings , 2008 .

[36]  Chyuan-Yow Tseng,et al.  Dynamic balancing scheme for motor armatures , 2007 .

[37]  F. M. Mitenkov,et al.  An algorithm for determination of the disbalance of a rotor with electromagnetic bearings , 2007 .

[38]  Xiangbo Xu,et al.  Automatic balancing of AMB systems using plural notch filter and adaptive synchronous compensation , 2016 .

[39]  Liangsheng Qu,et al.  THE OPTIMIZATION TECHNIQUE-BASED BALANCING OF FLEXIBLE ROTORS WITHOUT TEST RUNS , 2000 .

[40]  Gang Liu,et al.  Unbalance vibration suppression for AMBs system using adaptive notch filter , 2017 .

[41]  R. Tiwari,et al.  Application of active magnetic bearings for in situ flexible rotor residual balancing using a novel generalized influence coefficient method , 2018, Inverse Problems in Science and Engineering.

[42]  Kejian Jiang,et al.  Multi-frequency periodic vibration suppressing in active magnetic bearing-rotor systems via response matching in frequency domain , 2011 .

[43]  Yang Liu,et al.  Research on Automatic Balance Control of Active Magnetic Bearing-Rigid Rotor System , 2019, Shock and Vibration.

[44]  Paolo Pennacchi,et al.  Application and Comparison of High Breakdown-Point and Bounded-Influence Estimators to Rotor Balancing , 2010 .

[45]  Lili Dong,et al.  Adaptive control of an active magnetic bearing with external disturbance. , 2014, ISA transactions.

[46]  Jun Ni,et al.  Robust Optimal Influence-Coefficient Control of Multiple-Plane Active Rotor Balancing Systems , 2002 .

[47]  Shiqiang Zheng,et al.  A Field Balancing Technique Based on Virtual Trial-Weights Method for a Magnetically Levitated Flexible Rotor , 2014 .