Active magnetic bearings (AMBs) have led to great progress in the field of rotating machinery due to their many advantages, such as their non-contact and non-lubrication properties. As the key component of an AMB actuator, the switching power amplifier has an important impact on the performance of magnetic bearings and rotating machinery. In this paper, the topologies of switching power amplifiers for AMBs are introduced. The traditional half-bridge topology and two newly proposed topologies—the three-phase-half-bridge and neutralized-sharing-bridge topology—are analyzed and discussed. The volume, current output performance and cost of the power amplifier with different topologies are comprehensively evaluated, providing a theoretical basis and guidance for the selection and design of the topology of switching power amplifiers for AMBs under different conditions.

Speaker recognition methods based on convolutional neural networks (CNN) have been widely used in the security field and smart wearable devices. However, the traditional CNN has many hyperparameters that are difficult to determine, making the model easily fall into local optimum or even fail to converge during the training process. Intelligent algorithms such as particle swarm optimization and genetic algorithms are used to solve the above problems. However, these algorithms perform poorly compared to the current emerging meta-heuristic algorithms. In this study, the dung beetle optimized convolution neural network (DBO-CNN) is proposed to identify the speakers for the first time, which is helpful in finding suitable hyperparameters for training. By testing the dataset of 50 people, it was demonstrated that the accuracy of the model was significantly improved by using this approach. Compared with the traditional CNN and CNN optimized by other intelligent algorithms, the average accuracy of DBO-CNN has increased by 1.22~4.39% and reached 97.93%.

The Maglev motor has the characteristics of high-speed and high-power density, and is widely used in compressors, molecular pumps and other high-speed rotating machinery. With the requirements of miniaturization and high speed of rotating machinery, the rotor of the maglev motor will operate above the bending critical speed, and the critical vibration control of the flexible rotor is facing challenges. In order to solve the problem of the critical vibration suppression of the maglev high-speed motor, the system model of the maglev motor is established, the rotordynamics of the flexible rotor are analyzed and the rotor model is modal truncated to reduce the order. Then, the μ–controller is designed, and the weighting functions are designed to deal with the modal uncertainty. Finally, an experimental platform of the maglev motor with the flexible rotor is built to verify the effect of the μ–control on the suppression of the critical vibration of the maglev rotor.

The sensitive membrane of capacitive ultrasonic transducers is quite crucial for their performances, which can affect sensitivity, bandwidth, acoustic impedance, etc. In this study, an air-coupled capacitive ultrasonic transducer array is proposed with sensitive materials of MXenes. The air-coupled ultrasonic array with a Ti3C2Tx diaphragm is designed and fabricated. The array is $4\times4$ in size, with a membrane radius of 1 mm and a central frequency of 112.5 kHz. The simulation and experiments of the array are carried out to analyze the effect of the transducer characteristics by direct current (dc) bias voltages and alternating current (ac) excitation. The transmitting and receiving performance of the designed array are tested, and the results demonstrate that the array has outstanding sound pressure level (SPL) and receiving sensitivity. The feasibility of using Ti3C2Tx as a capacitive ultrasonic transducer diaphragm is indicated in this article, which expands the potential applications in acoustic measurement, detection, and imaging.