Recently, magnetic bearings have been widely used in inertial actuators of spacecraft. Aiming at the problem of unbalanced vibration in magnetically suspended system, the research status of active vibration control method is described in detail. Firstly, the structure and working principle of magnetically suspended system are introduced, and the causes of unbalanced vibration are expounded. Then, the research status of active vibration control methods at home and abroad is introduced from two aspects of synchronous vibration and harmonic vibration, and the advantages and disadvantages of each control method are summarized. Finally, the future development trend of active vibration control technology for magnetically suspended system is prospected.

To effectively recognize the incipient potential faults caused by degradation of multiple components in DC-DC converters, a fault diagnosis method that involves multi-dimensional feature fusion and sensitive feature extraction is proposed. Firstly, the time-domain statistical characteristics of fault and normal samples are extracted. The KL divergence and normalized kurtosis of intrinsic mode functions (IMFs) between them are calculated by empirical mode decomposition (EMD). In order to further improve the feature discrimination, a sensitive feature extraction method based on Mahalanobis distance (SFMD) is designed to screen out the key features. Finally, the sensitive features are used to construct the SA-LSSVM (Simulated annealing-Least squares support vector machine) model to realize the fault diagnosis. The accuracy of fault diagnosis in simulation and hardware experiment are 99.61% and 97.93% respectively. Compared with other fault diagnosis and feature selection methods, the proposed method still has higher accuracy and better engineering practicability.

In order to eliminate the influence of synchronous harmonic current caused by mass imbalance of magnetic bearing on attitude angular velocity measurement accuracy, a notch filter which can adjust the notch depth and center frequency is proposed. Firstly, the influence of synchronous harmonic current on the measurement accuracy of magnetically suspended control and sensitive gyroscope(MSCSG) is analyzed, and then a notch filter is designed which can adjust the notch depth and center frequency, and the measurement accuracy and stability of the system after eliminating synchronous harmonic current are analyzed. Simulation results show that the proposed method can effectively suppress the unbalance vibration torque and eliminate synchronous harmonic current. Finally, the correctness and effectiveness of the proposed method are verified by experiments. Experimental results show that the proposed method can reduce the vibration torque by 50% and improve the measurement accuracy of attitude angular velocity significantly.

DC-DC converter is the vital part of the power system, and its fault can cause the failure of complex electronic equipment. Therefore, the timely and accurate fault diagnosis of DC-DC converter is particularly important. This paper proposes a DC-DC converter fault diagnosis method based on improved SE-ResNet algorithm. First, in order to extract all information about the signals, we transform the one-dimensional signal into Gramian angular differential field (GADF) images. Then, the Squeeze-and-Excitation (SE) network is added to ResNet-50, combined with h-swish function and label smoothing cross entropy loss function (LSCE) to improve the model performance. In addition, simplify the redundancy layer of the network and achieve lightweight to improve the training efficiency. In the end, the logsoftmax is used for evaluating the effectiveness of the proposed method. The simulation experimental accuracy is up to 99.3220%,which is higher than other five classical deep learning algorithms. The hardware experiment also denotes the engineering practicability of the proposed method.

In order to solve the problem of poor precision in traditional modeling of DC-DC converter, an adaptive update method of digital twin based on mechanism-data drive is proposed in this paper to build a high-fidelity digital twin model. Firstly, a digital twin modeling method based on hybrid drive of mechanism-data driven model is proposed. The data-driven model based on Gate Recurrent Unit (GRU) is constructed to compensate the mechanism model in parallel. The virtual-real error can be reduced to 0.11%, which effectively improves the precision of digital twin modeling. Secondly, in order to solve the problem of model tracking accuracy reduction caused by component degradation, parameter identification of digital twin model based on Genetic Algorithm (GA) is proposed. The relative error of the identification results is close to 5%, which can realize the adaptive updating of the model. Finally, the fault prediction model of CNN-LSTM (Convolutional Neural Networks-Long short-term memory) based on high fidelity digital twin model is constructed to realize degradation trend prediction and fault warning of electrolytic capacitors.

A high-precision attitude-rate measurement of Magnetically Suspended Control & Sensing Gyroscope (MSCSG) using Variational Mode Decomposition (VMD) and Wavelet Transform (WT) is proposed in this paper, to aim at the influence of tilt current and tilt signal noise of MSCSG on attitude angular-rate measurement accuracy of spacecraft. Firstly, the sensitive model based on Lorentz torquer force is established, and the composition of rotor tilt signal is analyzed. The basic principle of modal decomposition of MSCSG tilt signal by VMD is introduced. A denoising method of MSCSG tilt signal based on improved VMD & WT is proposed. The number of mode decomposition is determined to improve VMD, by analyzing the frequency domain characteristics of tilt signal. WT is used to denoise the irrelevant mode obtained from VMD, and the signal is reconstructed by combining the denoising result and the relevant mode. Finally, simulation and experiments show that the proposed method has a good denoising effect on the tilt signal of MSCSG, and the angular-rate measurement accuracy of MSCSG can be improved by 16.2%.