Identification of bearing dynamic parameters and unbalance states in a flexible rotor system fully levitated on active magnetic bearings

Tiwari, Rajiv; Chougale, Avinash

doi:10.1016/j.mechatronics.2014.02.010

Cited by 75 publications

(31 citation statements)

References 14 publications

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“…In this model we have considered unbalance forces, inertia forces, gyroscopic effects and AMB forces. Equations of motion are given as follows [23] …”

Section: Model Descriptions and Development Of Identification Algorithmsmentioning

confidence: 99%

Estimation of speed-dependent bearing dynamic parameters in rigid rotor systems levitated by electromagnetic bearings

Tiwari

Talatam

2015

Mechanism and Machine Theory

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“…In this model we have considered unbalance forces, inertia forces, gyroscopic effects and AMB forces. Equations of motion are given as follows [23] …”

Section: Model Descriptions and Development Of Identification Algorithmsmentioning

confidence: 99%

Estimation of speed-dependent bearing dynamic parameters in rigid rotor systems levitated by electromagnetic bearings

Tiwari

Talatam

2015

Mechanism and Machine Theory

Self Cite

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“…Rotor dynamic balancing control is an important research content of rotating machinery vibration detection and control [1]. On the aspect of the rotor dynamic balancing control, the key problem is how to improve the balance accuracy and balance efficiency of the control strategy [2].…”

Section: Introductionmentioning

confidence: 99%

Rotor dynamic balancing control method based on fuzzy auto-tuning single neuron PID

Zhao

Jia

et al. 2017

IEICE Electron. Express

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In order to improve the control efficiency and balance accuracy of rotor automatic balance, a fuzzy self-tuning single neuron PID control method is proposed in this paper. Based on the single neuron PID control method, the fuzzy control theory is introduced to adjust the output gain K of single neuron PID control to realize single neuron PID control with variable step size. In order to verify the superiority of this method, the method we designed in this paper is compared with the traditional PID control method and the single neuron PID control method by the simulation and self-built experimental platform. Experiments and simulation results show that the fuzzy self-tuning single neuron PID control method has faster response time, less overshoot amount and fewer oscillation times than the traditional PID control method and the single neuron PID control method, and has strong robustness and good stability.

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“…Accurate models obtained by system identification are needed in order to design high-performance controllers (Noshadi et al, 2016), and they have an increasingly important role for diagnostic (Schuhmann et al, 2012) and monitoring purposes (Quinn et al, 2005), (Aenis et al, 2002), (Tiwiri and Chougale, 2014). A common choice for the excitation signal is a sine-wave-based spectrally rich signal, such as a multisine or swept sinusoid signal with a frequency content covering the desired frequency bands.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Excitation Signals in Active Magnetic Bearing System Identification

Vuojolainen¹,

Nevaranta²,

Jastrzębski³

et al. 2017

MIC

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Active magnetic bearings (AMBs) offer frictionless suspension, vibration insulation, programmable stiffness, and damping, among other advantages, in levitated rotor applications. However, AMBs are inherently unstable and require accurate system models for the high-performance model-based multi-input multi-output control of rotor position. Control electronics with high calculation capacity and accurate sensors of AMBs provide an opportunity to implement various identification schemes. A variety of artificial excitation signal-based identification methods can thus be achieved with no additional hardware. In this paper, a selection of excitation signals, namely the pseudorandom binary sequence (PRBS), chirp signal, multisine, and stepped sine are presented, applied, and compared with the AMB system identification. From the identification experiments, the rotor-bearing system, the inner current control loop, and values of position and current stiffness are identified. Unlike recently published works considering excitation-based identification of AMB rotor systems, it is demonstrated that identification of the rotor system dynamics can be carried out using various well-established excitation signals. Application and feasibility of these excitation signals in AMB rotor systems are analyzed based on experimental results.

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Identification of bearing dynamic parameters and unbalance states in a flexible rotor system fully levitated on active magnetic bearings

Cited by 75 publications

References 14 publications

Estimation of speed-dependent bearing dynamic parameters in rigid rotor systems levitated by electromagnetic bearings

Estimation of speed-dependent bearing dynamic parameters in rigid rotor systems levitated by electromagnetic bearings

Rotor dynamic balancing control method based on fuzzy auto-tuning single neuron PID

Comparison of Excitation Signals in Active Magnetic Bearing System Identification

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