In the development of hexagonal boron nitride (h-BN)-based polymeric composites with high thermal conductivity, it is always challenging to achieve a dense filling of h-BN fillers to form a desired high-density thermal transfer network. Here, a series of boron nitride nanosheets (BNNSs)/epoxy resin (EP) bulk composites filled with ultrahigh BNNSs content (65−95 wt %) is successfully constructed through a well-designed mechanical-balling prereaction combined with a general pressure molding method. By means of this method, the highly filled BNNSs fillers are uniformly dispersed and strongly bonded with EP within the composites. As a result, the densely BNNSs-filled composites can exhibit multiple performances. They have excellent mechanical properties, and their maximum compression strength is 30−97 MPa. For a BNNSs/EP composite with filling ultrahigh BNNSs fraction up to 90 wt %, its highly in-plane thermal conductivities (TC) are 6.7 ± 0.1 W m −1 K −1 (at 25 °C) to 8.7 ± 0.2 W m −1 K −1 (200 °C), respectively. In addition, the minimum coefficient of thermal expansion of BNNSs/EP composites is 4.5 ± 1.3 ppm/°C (only ∼4% of that of the neat EP), while their dielectric constants are basically located between 3−4 along with their dielectric loss tangent values exceptionally <0.3 in the ultrahigh frequency range of 12−40 GHz. Additionally, these BNNSs/EP composites exhibit remarkable cycle stability in heat transfer during heating and cooling processes because of their structural robustness. Thus, this type of densely BNNSs-filled BNNSs/ EP composite would have great potential for further practical thermal management fields.

Induction motors are mainstay power components in industrial equipment. Fault diagnosis technology of induction motors can detect the incipient fault and avoid the unplanned shutdown. The broken rotor bar is a significant fault mode of induction motors. Classical fault diagnosis methods always have complex principles and high computational costs, which leads to difficulties in understanding and calculation. In this paper, a method of broken rotor bar diagnosis based on the sum-of-squares of current signals is proposed. This method can eliminate the fundamental frequency and extract the signature frequency components by calculating the sum-of-squares of three-phase current signals. The signature frequency components are more apparent in the spectrum of the sum-of-squares of current signals. The effectiveness of the proposed method under different load levels and rotation motor speeds has been validated by two experiments. Compared with the classical diagnostic methods, the proposed method has better effectiveness and lower computation cost.

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