TFN: An Interpretable Neural Network with Time-Frequency Transform Embedded for Intelligent Fault Diagnosis

Convolutional Neural Networks (CNNs) are widely used in fault diagnosis of mechanical systems due to their powerful feature extraction and classification capabilities. However, the CNN is a typical black-box model, and the mechanism of CNN's decision-making are not clear, which limits its application in high-reliability-required fault diagnosis scenarios. To tackle this issue, we propose a novel interpretable neural network termed as Time-Frequency Network (TFN), where the physically meaningful time-frequency transform (TFT) method is embedded into the traditional convolutional layer as an adaptive preprocessing layer. This preprocessing layer named as time-frequency convolutional (TFconv) layer, is constrained by a well-designed kernel function to extract fault-related time-frequency information. It not only improves the diagnostic performance but also reveals the logical foundation of the CNN prediction in the frequency domain. Different TFT methods correspond to different kernel functions of the TFconv layer. In this study, four typical TFT methods are considered to formulate the TFNs and their effectiveness and interpretability are proved through three mechanical fault diagnosis experiments. Experimental results also show that the proposed TFconv layer can be easily generalized to other CNNs with different depths. The code of TFN is available on https://github.com/ChenQian0618/TFN.Comment: 20 pages, 15 figures, 5 table

Self-Compensating Liquid-Repellent Surfaces with Stratified Morphology.

Artificial liquid-repellent surfaces have recently attracted vast scientific attention; however, achieving mechanical robustness remains a formidable challenge before industrialization can be realized. To this end, inspired by plateaus in geological landscapes, a self-compensating strategy is developed to pave the way for the synthesis of durable repellent surfaces. This self-compensating surface comprises tall hydrophobic structural elements, which can repel liquid droplets. When these elements are damaged, they expose shorter structural elements that also suspend the droplets and thus preserve interfacial repellency. An example of this plateau-inspired stratified surface was created by three-dimensional (3D) direct laser lithography micro-nano fabrication. Even after being subjected to serious frictional damage, it maintained static repellency to water with a contact angle above 147° and was simultaneously able to endure high pressures arising from droplet impacts. Extending the scope of nature-inspired functional surfaces from conventional biomimetics to geological landscapes, this work demonstrates that the plateau-inspired self-compensating strategy can provide an unprecedented level of robustness in terms of sustained liquid repellency

Analysis on Safety Measures of Substation Maintenance

As an important node in the power grid, substation plays a very important role in the whole power grid. The equipment operation of the substation is carried out in order to timely and effectively detect the operation status of the equipment, find the latent fault of the equipment, and the maintenance of the substation is necessary for safe operation. However, there are some safety problems in the operation of the substation, which need to analyze the status quo of its safe operation and formulate the corresponding improvement measures. Based on this, this article on the substation maintenance work safety measures for a brief analysis, hoping to provide for future reference

Onset mechanism of an inverted U-shaped solar filament eruption revealed by NVST, SDO, and STEREO-A observations

Utilizing observations from the New Vacuum Solar Telescope (NVST), Solar Dynamics Observatory (SDO), and Solar Terrestrial Relations Observatory-Ahead (STEREO-A), we investigate the event from two distinct observational perspectives: on the solar disk using NVST and SDO, and on the solar limb using STEREO-A. We employ both a non-linear force-free field model and a potential field model to reconstruct the coronal magnetic field, aiming to understand its magnetic properties. Two precursor jet-like activities were observed before the eruption, displaying an untwisted rotation. The second activity released an estimated twist of over two turns. During these two jet-like activities, Y-shaped brightenings, newly emerging magnetic flux accompanied by magnetic cancellation, and the formation of newly moving fibrils were identified. Combining these observational features, it can be inferred that these two precursor jet-like activities released the magnetic field constraining the filament and were triggered by newly emerging magnetic flux. Before the filament eruption, it was observed that some moving flows had been ejected from the site as the onset of two jet-like activities, indicating the same physical process as two jet-like activities. Extrapolations revealed that the filament laid under the height of the decay index of 1.0 and had strong magnetic field (540 Gauss) and a high twisted number (2.4 turns) before the eruption. An apparent rotational motion was observed during the filament eruption. We deduce that the solar filament, exhibiting an inverted U-shape, is a significantly twisted flux rope. The eruption of the filament was initiated by the release of constraining magnetic fields through continuous magnetic reconnection. This reconnection process was triggered by the emergence of newly magnetic flux.Comment: 18 pages, 12 figures, accepted for publication in Astronomy & Astrophysic

The diploid genome sequence of an Asian individual

Here we present the first diploid genome sequence of an Asian individual. The genome was sequenced to 36-fold average coverage using massively parallel sequencing technology. We aligned the short reads onto the NCBI human reference genome to 99.97% coverage, and guided by the reference genome, we used uniquely mapped reads to assemble a high-quality consensus sequence for 92% of the Asian individual's genome. We identified approximately 3 million single-nucleotide polymorphisms (SNPs) inside this region, of which 13.6% were not in the dbSNP database. Genotyping analysis showed that SNP identification had high accuracy and consistency, indicating the high sequence quality of this assembly. We also carried out heterozygote phasing and haplotype prediction against HapMap CHB and JPT haplotypes (Chinese and Japanese, respectively), sequence comparison with the two available individual genomes (J. D. Watson and J. C. Venter), and structural variation identification. These variations were considered for their potential biological impact. Our sequence data and analyses demonstrate the potential usefulness of next-generation sequencing technologies for personal genomics