Guangwei Yu

Bearing fault identification and analysis is an important research area in the field of machinery fault diagnosis. Aiming at the common faults of rolling bearings, we propose a data-driven diagnostic algorithm based on the characteristics of bearing vibrations called multi-size kernel based adaptive convolutional neural network (MSKACNN). Using raw bearing vibration signals as the inputs, MSKACNN provides vibration feature learning and signal classification capabilities to identify and analyze bearing faults. Ball mixing is a ball bearing production quality problem that is difficult to identify using traditional frequency domain analysis methods since it requires high frequency resolutions of the measurement signals and results in a long analyzing time. The proposed MSKACNN is shown to improve the efficiency and accuracy of ball mixing diagnosis. To further demonstrate the effectiveness of MSKACNN in bearing fault identification, a bearing vibration data acquisition system was developed, and vibration signal acquisition was performed on rolling bearings under five different fault conditions including ball mixing. The resulting datasets were used to analyze the performance of our proposed model. To validate the adaptive ability of MSKACNN, fault test data from the Case Western Reserve University Bearing Data Center were also used. Test results show that MSKACNN can identify the different bearing conditions with high accuracy with high generalization ability. We presented an implementation of the MSKACNN as a lightweight module for a real-time bearing fault diagnosis system that is suitable for production.

KDP crystals have important applications in inertial confinement fusion. However, during the rapid growth of large-sized KDP crystals, inclusion is prone to occur. The existence of inclusion will lead to the reduction of crystal quality and utilization and even the end of the growth process. The generation of inclusion is related to the interaction between the crystal and the liquid flow. In this paper, we changed the hydrodynamic condition around the crystal by changing the crystal growth direction and achieve the rapid growth of [101] direction KDP crystals without inclusion at a low rotation rate. The utilization of the crystal was improved and the crystal has good optical transmittance, crystalline perfection and laser damage threshold. Meanwhile, atomic force microscopy was used to study the characteristics and changes of the micromorphology on (100) and (101) faces under different levels of supersaturation. The analysis results show that under high supersaturation, the uneven distribution of solutes and insufficient flow rate cause local macrosteps, two-dimensional step platforms and two-dimensional cores to form irregular structures with large slopes, thereby reducing the stability of the interface. This study will help to better understand the effect of the interaction between liquid flow and crystals on the formation of inclusion and guide the growth of KDP crystals.

Potassium dihydrogen phosphate crystals were grown around 65 °C. The growth rate of KDP (KH₂PO₄) crystal prismatic faces was measured by laser polarization interference system. The surface micro morphology of KDP crystals grown at various supersaturation were comparatively observed by atomic force microscope systematically. The results show that the growth rate increased with the rise of supersaturation, the aspect ratio reduced. The steps bunching height occurred at σ = 0.03 and 0.04. At this point, the steps height reached maximum value about 11.3~24.4 nm. The step bunching was almost constant at higher supersaturation. A few pits and holes appeared on the crystal surface at high supersaturation. In our opinion, the forming of these pits and holes might be related with the step movement and 2D nuclei mechanism.

A novel scaly Sn₃O₄/TiO₂ nanobelt heterostructured photocatalyst was fabricated via a facile hydrothermal route. The scaly Sn₃O₄ nanoflakes can be synthesized in situ and assembled on surface coarsened TiO₂ nanobelts through a hydrothermal process. The morphology and distribution of Sn₃O₄ nanoflakes can be well-controlled by simply tuning the Sn/Ti molar ratio of the reactants. Compared with single phase nanostructures of Sn₃O₄ and TiO₂, the scaly hybrid nanobelts exhibited markedly enhanced photoelectrochemical (PEC) response, which caused higher photocatalytic hydrogen evolution even without the assistance of Pt as a co-catalyst, and enhanced the degradation ability of organic pollutants under both UV and visible light irradiation. In addition to the increased exposure of active facets and broad light absorption, the outstanding performance is ascribed to the matching energy band structure between Sn₃O₄ and TiO₂ at the two sides of the heterostructure, which efficiently reduces the recombination of photo-excited electron–hole pairs and prolongs the lifetime of charge carriers. Both photocatalytic assessment and PEC tests revealed that Sn₃O₄/TiO₂ heterostructures with a molar ratio of Sn/Ti of 2/1 exhibited the highest photocatalytic activity. This study provides a facile and low-cost method for the large scale production of Sn₃O₄ based materials in various applications.