Magnetic concrete (MC) containing cement and magnetic particles is gaining increasing attention. Current research on improving MC permeability mainly focuses on adopting high-performance materials and adjusting magnetic particle sizes and proportions. These methods are effective but often result in increased costs. Enhancing magnetic materials’ anisotropy can improve permeability without adding additional cost. However, existing research has been relatively insufficient in exploring this issue. This paper proposes to use pulsed electromagnetic fields to improve the anisotropy of MC, thereby increasing the permeability. The results indicate that pulses can enhance the permeability (µr) of magnetic cores made of particle material by 8.12 % to 24.58 %, depending on the particle size, and increase the permeability of magnetic cores made of MC by 2.79 % without increasing costs.

A fault-tolerant strategy is proposed in this paper for the soft start of an inductor motor using a fully-controlled power semiconductor-based soft starter when it experiences a short-circuit switch fault. The proposed strategy aims to reduce transient torque pulsations, balance and lower inrush current without incurring extra hardware costs, thereby enhancing the reliability and tolerant capability of the soft starter system. Initially, the fault-tolerant soft start modulation in the event of a short-circuit switch fault is presented. Subsequently, a mathematical analysis is introduced to guide the selection of initial firing angles for the healthy phases in the context of a short-circuit switch fault. Additionally, a small-signal model is established, and system stability is verified based on a closed-loop fault-tolerant control system. Finally, simulation and experimental results validate the effectiveness of the proposed fault-tolerant strategy in the fully-controlled power semiconductor-based soft starter system. The balanced inrush current decreases by approximately 13.5%, and the transient torque pulsations decrease by around 16% compared to the soft start method without employing the proposed fault-tolerant strategy.

Fully-controlled power semiconductor device-based solid-state circuit breaker (SSCB) not only features fast fault interruption, arcless, noiseless, and no moving parts, but also has the capability to integrate functions of a soft starter, circuit breaker, contactor, and thermal relay in motor control center applications. This paper focuses on optimizing the soft start control method of SSCBs based on fully-controlled power semiconductors and proposes a constant transient current control strategy. Motor phase-to-neutral voltage and current expressions during the soft starting process are analyzed. Then, a transfer function is developed for the closed-loop control system with the effective value of motor current as a reference, along with its small-signal model. Furthermore, the control system stability and controller parameter selection are analyzed. Finally, the effectiveness of the proposed control solution is verified by both simulation and experimental results. The soft start time of the proposed solution is 5 s, which is less than half of the open-loop scheme’s 10.6 s, demonstrating a reduction of over 50% in soft start time.

AC series arc is dangerous and can cause serious electric fire hazards and property damage. This article proposed a convolutional neural network -based arc detection model named ArcNet. The database of this research is collected from eight different types of loads according to IEC62606 standard. The two most common types of arcs, including arcs from a loose connection of cables and those caused by the failure of the insulation, are generated in testing and included in the database. Using the database of raw current, experimental results indicate ArcNet can achieve a maximum of 99.47% arc detection accuracy at 10 kHz sampling rate. The model is also implemented in Raspberry Pi 3B for classification accuracy. A tradeoff study between the arc detection accuracy and model runtime has been conducted. The proposed ArcNet obtained an average runtime of 31 ms/sample of 1 cycle at 10 kHz sampling rate, which proves the feasibility of practical hardware deployment for real-time processing.