Vibration Control of Active Magnetic Bearing using Kalman Filter

2018 ◽  
Vol 2018.67 (0) ◽  
pp. 112
Author(s):  
Kazushige Yoshino ◽  
Gan Chen ◽  
Isao Takami
Keyword(s):  
Kalman Filter ◽  
Vibration Control ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing

scholarly journals Research on Automatic Balance Control of Active Magnetic Bearing-Rigid Rotor System

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Yang Liu ◽  
Shuaishuai Ming ◽  
Siyao Zhao ◽  
Jiyuan Han ◽  
Yaxin Ma
Keyword(s):  
Vibration Control ◽  
Rotational Speed ◽  
Notch Filter ◽  
Magnetic Bearing ◽  
Rotor System ◽  
Vibration Response ◽  
Active Magnetic Bearing ◽  
Rigid Rotor ◽  
Phase Compensation ◽  
Synchronous Control

In this paper, in order to solve the problem of unbalance vibration of rigid rotor system supported by the active magnetic bearing (AMB), automatic balancing method is applied to suppress the unbalance vibration of the rotor system. Firstly, considering the dynamic and static imbalance of the rotor, the detailed dynamic equations of the AMB-rigid rotor system are established according to Newton’s second law. Then, in order to rotate the rotor around the inertia axis, the notch filter with phase compensation is used to eliminate the synchronous control current. Finally, the variable-step fourth-order Runge–Kutta iteration method is used to solve the unbalanced vibration response of the rotor system in MATLAB simulation. The effects of the rotational speed and phase compensation angle on the unbalanced vibration control are analysed in detail. It is found that the synchronous control currents would increase rapidly with the increase of rotational speed if the unbalance vibration cannot be controlled. When the notch filter with phase shift is used to balance the rotor system automatically, the control current is reduced significantly. It avoids the saturation of the power amplifier and reduces the vibration response of the rotor system. The rotor system can be stabilized over the entire operating speed range by adjusting the compensation phase of the notch filter. The method in the paper is easy to implement, and the research result can provide theoretical support for the unbalance vibration control of AMB-rotor systems.

The Oil-Free Shaft Line

1988 ◽  
Author(s):  
Bruno Wagner
Keyword(s):  
Vibration Control ◽  
Magnetic Bearing ◽  
Magnetic Bearings ◽  
Active Magnetic Bearing ◽  
Active Magnetic Bearings ◽  
Present Stage ◽  
Shaft Line ◽  
Process Gas ◽  
Gas Seals ◽  
Length Reduction

This paper recalls the principles and main features of the active magnetic bearings and especially the advantages for turbomachines. Oil-free working and vibration control are part of them. Field experiences are described for different shaft line configurations. Step by step we are going to get totally rid of oil with the introduction of active magnetic bearings together with dry gas seals and gearless drive. Future machines will take the benefit of all this field experience. The trend of the design optimization is the active magnetic bearings in the process gas itself, for a length reduction of shafts. But at the present stage, the active magnetic bearing is a proven technology today.

Nonlinear adaptive harmonics vibration control for active magnetic bearing system with rotor unbalance and sensor runout

2021 ◽  
pp. 1-1
Author(s):  
Huijuan Zhang ◽  
Jianjuan Liu ◽  
Ruipu Zhu ◽  
Hongmei Chen ◽  
Hang Yuan
Keyword(s):  
Vibration Control ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Bearing System

Intelligent Kalman Filtering for Fault Detection on an Active Magnetic Bearing System

2008 ◽  
Author(s):  
Nana K. Noel ◽  
Kari Tammi ◽  
Gregory D. Buckner ◽  
Nathan S. Gibson
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Fault Detection ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Estimation Accuracy ◽  
False Alarms ◽  
Single Input Single Output ◽  
Single Output ◽  
Modeling Uncertainties

One of the challenges of condition monitoring and fault detection is to develop techniques that are sufficiently sensitive to faults without triggering false alarms. In this paper we develop and experimentally demonstrate an intelligent approach for detecting faults in a single-input, single-output active magnetic bearing. This technique uses an augmented linear model of the plant dynamics together with a Kalman filter to estimate fault states. A neural network is introduced to enhance the estimation accuracy and eliminate false alarms. This approach is validated experimentally for two types of fabricated faults: changes in suspended mass and coil resistance. The Kalman filter alone is shown to be incapable of identifying all fault cases due to modeling uncertainties. When an artificial neural network is trained to compensate for these uncertainties, however, all fault conditions are identified uniquely.

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