Recent research has increasingly focused on non-intrusive fault diagnosis of servo system components using rotor speed signals. This paper introduces a gearbox fault detection method for drive chains based on motor speed signals, suitable for variable speed operation. In this innovative alternative, a dual-domain separation deconvolution algorithm is proposed. First, mathematical modeling and analytical investigation are conducted on the characteristic behaviors of gear faults, specifically focusing on tooth breakage and wear conditions. Second, gear fault features in speed signals are reconstructed under dynamic speed conditions via the proposed dual-domain separation deconvoluction method. Then, gear health status is determined by comparing the extracted fault features with the known transmission ratio parameters. Finally, experimental results demonstrate the effectiveness of the proposed method for gear fault diagnosis under variable-speed conditions. The proposed fault diagnosis strategy has significant application potential in servo safety monitoring field, particularly in scenarios where vibration sensor installation is impractical.

In this work, the surge current ruggedness (the ability to withstand the surge current until failure happens) in the third-quadrant is investigated for evaluating the reliability of the SiC MOSFET. A dynamic surge test platform (DSTP) is developed, and the surge trajectories are observed in detail. It is found that the source-drain current is mainly carried by the body diode of SiC MOSFET during the surge event, regardless of the gate-source voltage is positive or negative. The gate-source terminals shorting and three-terminals shorting are two surge failure modes of the SiC MOSFET, which depend on the shocking strength of the surge power. Furthermore, the oscillation induced by dynamic avalanche effect (DAE) is observed in the surge test, which expands the understandings about the negative effect of surge event. This work is aimed to give the useful knowledge about the surge current ruggedness, and some practical suggestions based on the experimental results are given out to improve the system reliability.

This paper proposes a non-invasive fault location method for modular multilevel converters (MMC) considering light load conditions. The prior-art fault location methods of the MMC are mostly developed under full load conditions. However, it is revealed that the faulty arm current will be suppressed to be unipolar when the open-circuit fault happens on the submodule switch under a light load. This leads to the capacitor voltage of the healthy and faulty submodules rising or falling with the same variations, increasing the difficulty of fault location. The proposed approach of injecting the second-order circulating current will rebuild the bipolar arm current of the MMC and enlarge the capacitor voltage deviations between the healthy and faulty SMs. As a result, the fault location time is significantly shortened. The simulations are carried out to validate the effectiveness of the proposed approach, showing that the fault location time is reduced to 1/6 compared with the condition without second-order circulating current injection.

Modular multilevel converter (MMC) is a promising converter in medium and high voltage applications due to its modularity and easiness to meet any voltage level by cascading the sub-modules. However, large amount of modules not only increase the failure probability of the devices, but also increase the difficulty of the fault diagnosis, which have brought a challenging for popularization and application of the MMC. Therefore, an extended state observer based fault diagnosis strategy for MMC is proposed in this paper. The extended state observer is designed based on the circulating current equation. The output of the extended state observer is compared with the theoretical value calculated by the modified switching models to locate the fault. The simulation is modeled and carried out in Matlab/Simulink. The effectiveness of the proposed strategy is verified by the simulation results.