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Frequency domain spectroscopy (FDS) is a common nondestructive test method for insulation diagnosis of a transformer. Rapid and accurate testing can help improve the efficiency of FDS. However, the long test duration of conventional FDS and the unsatisfactory accuracy of existing accelerated FDS methods limit the application of insulation conditions of transformers. To tackle these problems, a new testing method named sFDS is proposed, aiming to achieve rapid and accurate testing. The proposed sFDS consists of two main parts to achieve the goal: first, the test duration is reduced by using sawtooth and regression analysis. Second, to ensure test accuracy, a multidomain signal accurate processing technique is proposed. Specifically, first, a filtering algorithm is used to isolate the noise. Second, the phase correction is used to improve the precision of time-frequency conversion. Third, the line interpolation method is utilized to accurately extract spectral data to compute dielectric loss and complex capacitance. To verify the practicality of sFDS, an sFDS test platform is built and compared with existing accelerated FDS techniques through practical experiments. The results indicate that sFDS performs superiorly in rapidity and accuracy. Meanwhile, sFDS has the potential to become a general method for evaluating more electrical objects.

The leakage flux controllable permanent magnet (LFC-PM) motor, which uses intentional magnet leakage flux paths cross-coupled with the q-axis flux paths to realize flux regulation, has been proposed recently and has received widespread attention for traction applications. Yet, the dual function of q-axis current, including flux regulation and torque generation, along with the resulting parameter variation caused by the controllable leakage flux, is one of the main barriers to its control and widespread application. To overcome this barrier, based on the model predictive current control, this article proposes a current decoupling control for the LFC-PM motor. The contribution of this paper is developing a virtual flux reference frame concept where the mathematic model and the optimal current assignment are deduced. On this basis, the predicted parameters can be obtained more accurately, which can suppress the disturbances and low efficiency caused by the mismatched parameters in the process of flux regulation. The proposed decoupling control is validated and compared with the traditional maximum torque per ampere methods. The effectiveness of the proposed control strategy is validated by means of experimental results on a test rig with a 3-kW leakage flux controllable PM motor.

There are significant couplings between control techniques and disturbance rejection techniques in traditional control schemes for systems with mismatched disturbances, such that both techniques have to be designed simultaneously. In this paper, independent of specific control methods, a universal disturbance rejection scheme named equilibrium compensation based control, is proposed for general systems to attenuate mismatched disturbances and sensor errors while retaining the nominal controller's performance. In addition, several criteria are provided to analyze the observability and compensability of the disturbances and sensor errors. Simulations and experiments of tracking tasks for a single-track-two-wheeled robot with four different controllers demonstrate the effectiveness of the proposed scheme.

With the extensive application of analog circuits in many electronic devices, it is important to achieve accurate alerts in the incipient fault stage of analog circuits to reduce the threat on their reliability. However, the faint nature of incipient faults and the tolerance of components lead identifying incipient faults as a huge research challenge. Consequently, a complex convolutional self-attention autoencoder (CCSAE) is proposed in this paper to perform incipient fault diagnosis for analog circuits, which contains a feature extraction module, a feature enhancement module, and a classification module. In the first module, a backbone based on the complex convolutional autoencoder (CCAE) is designed to provide effective feature representations containing the amplitude information and phase information of analog circuit responses. In the feature enhancement module, a complex self-attention layer is constructed to enhance the useful structural information for feature representations by capturing internal correlations, thus addressing the faint nature of incipient faults. Finally, a two-step training mechanism including feature training and classification training is designed for CCSAE, where the key operation is the construction of supervised contrast loss (SCL) to pull closer similar feature representations and push away dissimilar ones. To demonstrate the effectiveness and merits of the proposed method, a typical Sallen–Key bandpass filter circuit and an actual amplifier board circuit of the water jet propulsion device are considered as experimental circuits. The experimental results indicate that this method achieves an average accuracy of 99.92% in the former and 98.25% in the latter, which is superior to other excellent methods.

As the representative energy-consuming equipment in the manufacturing industry, machine tools consume lots of energy during the nonmachining period, which leads to low energy efficiency. The existing strategies do not consider the startup sequence among components, which causes the control parameters to fail to run during the practical startup process, and this paper conducts energy-saving research to address the issues. The relationship of priority among components was used as the constraint to obtain an energy-saving control strategy for multisleep states of machine tools considering components priority. Furthermore, the improved whale algorithm was applied to solve the energy-saving control strategy of the machine tool, and the search and convergence ability of the algorithm was improved by introducing the chaotic convergence factor and adaptive weight coefficient. Finally, the energy-saving strategy was utilized with a vertical CNC machine tool as an experimental example to mill the end face of the randomly arriving workpieces. The results show that this changed algorithm has a better solution speed and effect than the ordinary whale algorithm and some other improved whale algorithms. Compared with the practical control process and other control strategies, the control strategy considering components priority can obtain more stable productivity and better energy-saving effect.

In this paper, a new nonisolated four-port dc–dc converter is proposed for dc microgrid applications. The proposed converter offers a main feature of controlling the dc link voltage regardless of resources availability. By using four IGBT switches and only one diode, three different sources can be interfaced to a boosted dc link load. Different operation modes of the proposed architecture are discussed, testified, and validated experimentally. The buck–boost capability of the proposed topology allows an enhanced flexibility to integrate various sources with distinct voltage-current (V–I) characteristics while sharing load power among all ports. In this context, steady state analysis is performed to determine the voltage gains between all ports. The control strategy is developed for the proposed topology to manage power flow between sources and load achieving basic operations for renewable resources such as MPPT for PV. A theoretical based study is performed on the proposed converter including steady-state analysis, state-space averaging followed by small signal modeling and frequency response-based controller design. The converter different operating conditions are validated experimentally.

One major challenge for the design of the rotary machine for electric propulsion aircraft is how to improve its torque output and power density. The objective of this paper is to propose a novel external blending-shaped tessellation (EBT) magnet pattern for electromagnetic rotary machine. It can offer several advantages. First, it helps to increase the magnetic flux density in the airgap, and thus the torque output is increased. Second, it enhances the self-shielding effect greatly, and thus the back iron can be removed completely and replaced with low-density materials. Third, the improved torque and the reduced mass may contribute to the high power density as well. The design concept and operating principle of the proposed magnet pattern are presented. Following that, the magnetic field distribution is formulated analytically. Then the torque generation of the machine is modeled mathematically. Subsequently, the numerical simulation is conducted to validate the analytical models. The magnetic flux density and torque output of the proposed magnet pattern are compared with those of conventional magnet arrays. A research prototype with the EBT magnet pattern is developed, and an experimental test platform is constructed. Experiments are conducted on the magnetic flux density and torque output to verify the proposed design and analytical models. The experimental results validate the derived analytical models and the effectiveness of the magnet array in improving the output characteristic. It shows that the output torque generated by the proposed design is larger than that of conventional Halbach arrays by 27 percent.

The trend toward intellectualization is pervasive in the field of power equipment fault diagnosis. However, due to the sample database's limitations, intelligent diagnosis of transformer insulation aging states near the internal hotspot regions remains a challenge. To address this issue, an optimization-design-based simulation model is proposed for the development of a frequency domain spectroscopy (FDS) database for diagnosing nonuniform aging states of power transformer. The simulation model is developed in the current work using distributed relaxation circuits and fast Fourier transforms, and the electric parameters used are identified using adaptive iteration particle swarm optimization. Finally, verification established that the extended simulation model was capable of simulating the FDS of a system with nonuniformly assigned aging states. In this regard, the contribution will aid in the establishment of a trustworthy FDS database for the purpose of advancing intelligent diagnosis of the aging state of transformer oil–paper insulation at hotspots.

For a class of industrial processes described by a second-order plus time delay model, this paper investigates the design of active disturbance rejection control (ADRC) incorporating model information. By using the low-frequency approximation, the lumped plant consisting of all internal loops can shape the closed-loop tracking dynamic to the expected response, allowing the feedback gains to be formulated by the desired tracking factor. In this framework, a rigorous stability criterion is first depicted intuitively in terms of dimensionless parameters. An explicit upper bound on the observer bandwidth is then analytically derived through an in-depth analysis of the decaying behavior in the magnitude of the loop function, which guarantees a more satisfactory margin for mismatched delays than existing related studies. Based on this constraint, the regulable tracking factor can further endow the ADRC system with comprehensive robustness to cope with other uncertainties. Comparative simulations and a water tank experiment reveal the merits of the proposed configuration. Furthermore, the field application of this method in the wet flue gas desulfurization process demonstrates its promising practical prospects.

Finite element analysis (FEA) has been used more frequently than ever before in electrical machine design covering different disciplines such as electromagnetics, rotor dynamics, thermodynamics, etc. The accuracy and speed of FEA are in high demand, especially when time-stepping FEA is employed in the electromagnetic design of the machine. In this article, to accelerate numerical transient in FEA of a voltage-driven permanent magnet synchronous machine, a fast ac steady-state algorithm has been proposed, in which the voltage supply is converted into the stator flux linkage and the machine can be regarded as driven by the flux linkage directly. The electromagnetic transient is eliminated by injecting additional voltage signals to compensate for the oscillating stator flux linkage in the transient and the time-stepping error caused by the backward Euler in FEA. And the additional voltage signals will finally disappear after the steady state is achieved within about a half electrical time period. In addition, the maximum torque per ampere control logic can also be realized by adjusting the initial phase angle of the voltage supply based on the vector diagram. The simulation speed of the proposed method in this paper was compared to other traditional models, and the accuracy was verified by experimental results.

Reliability and efficiency improvements of photovoltaic (PV) inverters have a high potential to decrease the cost of PV energy. Discontinuous pulse width modulation (DPWM) is an effective method to improve both the efficiency and reliability of the power devices of the single-phase five-level T-type neutral point clamped (NPC) inverter. However, applying DPWM gives a negative effect on the lifetime of the dc-link capacitors and thus, reduces the reliability of the inverter from the system-level reliability point of view. This paper proposes the DPWM strategy to improve the lifetime of the dc-link capacitor compared with the conventional DPWM method so that both reliability and efficiency of the single-phase five-level T-type NPC inverter are improved. Through the proposed strategy, the lifetime of the dc-link capacitor is improved, but its negative effects on the efficiency of the inverter and the lifetime of the power devices are negligible. Therefore, the advantages of applying DPWM can be sustained. Simulation and experimental results verify the feasibility and effectiveness of the proposed DPWM strategy.

Theorem 1 in the discussed paper is shown to be incorrect by means of a simple counterexample. The example shows that the semi-implicit conditioned super-twisting algorithm does not admit a general tuning rule for its parameter $\kappa _{1}$ that can guarantee the same control accuracy as in the absence of actuator saturation.