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Summary of Research on Unbalanced Vibration Control of Magnetic Levitation Rotors (III)

Release time:

2023-01-13

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2.2.2 Phase estimation for rotor imbalance compensation

The phase of the rotor imbalance compensation signal determines the direction of the imbalance compensation force. In an ideal state, the compensation force should be equal to the opposite direction of the imbalance force. Due to the unbalanced force acting on the magnetic levitation rotor, the rotor vibrates. The same frequency displacement of the unbalanced vibration of the magnetic levitation rotor is a sine signal, in the form of X (t)=Asin( ω T+ φ)。 Therefore, existing methods often use the reference signal method to estimate the imbalance compensation phase, obtain real-time displacement information of the rotor through displacement sensors, extract the same frequency vibration displacement generated by the imbalance vibration, and use this as a reference signal to obtain phase information. Currently, the commonly used algorithms include LMS algorithm, notch filter algorithm, iterative approximation algorithm based on Fourier coefficients, filtering algorithm, etc.

Reference [26] proposes an LMS algorithm based on frequency domain adaptation. The block diagram of single channel unbalanced vibration adaptive control is shown in Figure 14, which takes harmonic vibration as input and references a sine signal with the same component as the sensor jump. Simulation results show that this method can effectively extract the unbalanced and frequency vibration signal of the magnetic levitation rotor.

Reference [38] proposes a fast phase tracking algorithm based on the LMS algorithm. The compensation algorithm framework is shown in Figure 15, which combines PID and variable step LMS algorithm control strategy, and adds a tracking algorithm to the filter until the rotor speed reaches a certain value. Real time experiments under the DSP architecture have verified the phase tracking performance of the algorithm.

The LMS algorithm is widely used in rotor imbalance compensation phase estimation and can be understood as a notch algorithm for specific frequency signals. In addition, there are other filtering algorithms used for compensating phase estimation of magnetic bearing rotor imbalance. Reference [39] uses the Kalman filter method to extract the amount of unbalanced displacement. According to the unbalanced displacement, the linear Gauss state feedback controller improves the stiffness and reduces the vibration. Reference [40] applies the synchronous rotating coordinate system (SRF), which is widely used in motor control, to magnetic bearing control. A feedforward control loop as shown in Figure 16 is used to construct two orthogonal signals through single-phase displacement error signals as input for SRF transformation. The same frequency displacement error is converted into direct flow, and the DC error after transformation is tracked and controlled without static error. Reference [41] proposes a phase compensation method to enhance the damping level of a flexible rotor near the first bending critical speed. By incorporating a phase compensation algorithm into the controller, the overall damping of the rotor system is increased. Simulation and experimental results show that phase compensation can significantly improve the first-order bending modal damping of the rotor, effectively suppress the resonance vibration of the rotor, and enable the rotor to pass through the first bending critical speed smoothly, Achieve supercritical operation.

2.3 Algorithm switching control

The bearing electromagnetic force small algorithm and the rotor displacement small algorithm are two completely opposite control methods, each with advantages and disadvantages. The bearing electromagnetic force small control algorithm has the problem of unstable closed-loop system at low speeds. Although the rotor displacement small algorithm can achieve high-precision rotation of the rotor, it is easy to cause power amplifier saturation and amplify rotor vibration phase and imbalance at high speeds