多共振分量融合CNN的行星齿轮箱故障诊断

针对行星齿轮箱中各部件所激起的振动成分混叠、早期故障特征经常被较强的各级齿轮谐波成分以及环境噪声所湮没的问题，提出一种多共振分量融合卷积神经网络（multi-resonance component fusion based convolutional neural network，简称MRCF-CNN）的行星齿轮箱故障诊断方法。首先，对振动信号进行共振稀疏分解，得到包含齿轮谐波成分的高共振分量和可能包含轴承故障冲击成分的低共振分量；其次，构建多共振分量融合卷积神经网络，将得到的高、低共振分量和原始振动信号进行自适应的特征级融合，通过有监督的方式训练模型并进行行星齿轮箱故障诊断。对行星齿轮箱实验数据的分析结果表明，该方法能够有效分类行星齿轮箱中滚动轴承和齿轮的故障，成功对行星齿轮箱故障进行诊断，同时能够进一步增强卷积神经网络对振动信号所蕴含的故障信息的辨识能力。     

Self-learning residual model for fast intra CU size decision in 3D-HEVC

As an extension of the High Efficiency Video Coding (HEVC) standard, 3D-HEVC requires to encode multiple texture views and depth maps, which inherits the same quad-tree coding structure as HEVC. Due to the distinct properties of texture views and depth maps, existing fast intra prediction approaches were presented for the coding of texture views and depth maps, respectively. To further reduce the coding complexity of 3D-HEVC, a self-learning residual model-based fast coding unit (CU) size decision approach is proposed for the intra coding of both texture views and depth maps. Residual signal, which is defined as the difference between the original luminance pixel and the optimal prediction luminance pixel, is firstly extracted from each CU. Since residue signal is strongly correlated with the optimal CU partition, it is used as the feature of each CU. Then, a self-learning residual model is established by intra feature learning, which iteratively learns the features of the previously encoded coding tree unit (CTU) generated by itself. Finally, a binary classifier is developed with the self-learning residual model to early terminate CU size decision of both texture views and depth maps. Experimental results show the proposed fast intra CU size decision approach achieves 33.3% and 49.3% encoding time reduction on average for texture views and depth maps with negligible loss of overall video quality, respectively.     

Robust image retrieval by cascading a deep quality assessment network

The performance of computer vision algorithms can severely degrade in the presence of a variety of distortions. While image enhancement algorithms have evolved to optimize image quality as measured according to human visual perception, their relevance in maximizing the success of computer vision algorithms operating on the enhanced image has been much less investigated. We consider the problem of image enhancement to combat Gaussian noise and low resolution with respect to the specific application of image retrieval from a dataset. We define the notion of image quality as determined by the success of image retrieval and design a deep convolutional neural network (CNN) to predict this quality. This network is then cascaded with a deep CNN designed for image denoising or super resolution, allowing for optimization of the enhancement CNN to maximize retrieval performance. This framework allows us to couple enhancement to the retrieval problem. We also consider the problem of adapting image features for robust retrieval performance in the presence of distortions. We show through experiments on distorted images of the Oxford and Paris buildings datasets that our algorithms yield improved mean average precision when compared to using enhancement methods that are oblivious to the task of image retrieval. ¹     

Flow control with electrode bank arrangements by electrohydrodynamics force for heat transfer enhancement in a porous medium

Active flow control with electrohydrodynamics (EHD) force in the channel flow has been numerically investigated for enhancing heat transfer. This study focuses on the effect of electrode bank arrangements and the number of electrodes on corona wind and fluid flow for heat transfer onto a porous medium. Aligned and staggered configurations of electrode banks are compared. The numerical results show that electric field intensity depends on electrical voltage and the number of electrodes. Shear flow is increased with larger numbers of electrodes and in the aligned configuration, resulting in the enhancement of vortex strength. The swirling flow from staggered configurations spread wider than that of aligned configurations, but the aligned configuration produced more turbulence. In addition, the temperature distribution in the channel flow is increased with increasing numbers of electrodes. With the effect of swirling flow, airflow above the porous sample surface is faster leads the heat to more transfer to the porous sample surface. This causes the temperature of porous medium to increase rapidly so the convective heat transfer coefficient on porous medium surface is increased. Finally, the modified case of the numerical results is validated against the experimental results. The experimental flow visualization is based on the incense smoke technique, in order to verify the accuracy of the swirling flow pattern subjected to the electric field. It is shown that the comparison results in both techniques are in good agreement.     

2-Aminobenzothiazoles Inhibit Virulence Gene Expression and Block Polymyxin Resistance in Salmonella enterica

One promising strategy to combat antibiotic-resistant bacteria is to develop compounds that block bacterial defenses against antibacterial conditions produced by the innate immune system. Salmonella enterica, which causes food-borne gastroenteritis and typhoid fever, requires histidine kinases (HKs) to resist innate immune defenses such as cationic antimicrobial peptides (CAMPs). Herein, we report that 2-aminobenzothiazoles block histidine kinase-dependent phenotypes in Salmonella enterica serotype Typhimurium. We found that 2-aminobenzothiazoles inhibited growth under low Mg²⁺, a stressful condition that requires histidine kinase-mediated responses, and decreased expression of the virulence genes pagC and pagK. Furthermore, we discovered that 2-aminobenzothiazoles weaken Salmonella’s resistance to polymyxin B and polymyxin E, which are last-line antibiotics and models for host defense CAMPs. These findings raise the possibilities that 2-aminobenzothiazoles can block HK-mediated bacterial defenses and can be used in combination with polymyxins to treat infections caused by Salmonella.     

Review of the phase change material (PCM) usage for solar domestic water heating systems (SDWHS)

The shortage in energy resources combined with the climb in greenhouse emissions is the main incentive beyond the deployment of solar energy resource in various applications. One of the most successful applications is the utilization of solar energy in the domestic water heating systems (DWHS) because 70% of the consumed energy in the residential segment is utilized for space heating and appliances in cold climates 1 . However, the full deployment of solar energy in domestic water heating is only possible when an energy storage system with acceptable price is available. Recently a new tendency for deploying phase change materials (PCMs) as an energy storage system is introduced in several solar DWHS. These systems are known as integrated PCM in solar DWHS and offer several advantages including high storage capacity, low storage volume, and isothermal operation during the charging and discharging phases. The present study reviews various techniques utilized for integrating the PCM in solar water heating systems and the utilized methods for enhancing the heat transfer characteristics of the PCM through the usage of extended surfaces and high conductive additives. Copyright © 2017 John Wiley & Sons, Ltd.     

基于局部放电法的矿用高压电缆信号去噪算法研究

干扰噪声直接影响局部放电法有效检测矿用高压电缆故障。基于局部放电法，综合采用理论计算、仿真实验、现场试验的方法，对比分析了短时傅里叶变换和傅里叶分析去噪法的原理和优缺点，提出了一种矿用高压电缆的局部放电去噪算法——小波阈值去噪法，同时，选择了合理的阈值函数和去噪流程。基于此，采用白噪声和连续周期信号作为高压电缆的干扰噪声，进行了模拟仿真实验。结果表明，小波阈值去噪法可有效抑制白噪声，其中，Db2小波性能和去噪效果最好；同时，现场试验结果显示，去噪后信噪比得到了显著增加，验证了小波阈值去噪法的合理性和可靠性。     

Numerical study on premixed hydrogen/air combustion characteristics and heat transfer enhancement of micro-combustor embedded with pin fins

Aimed at improving the energy output performance of the Microthermal Photovoltaic (MTPV) system, it is necessary to optimize the structure of the micro combustor. In this paper, micro combustor with in-line pin fins arrays (MCIPF) and micro combustor with both end-line pin fins arrays (MCEPF) were presented to realize the efficient combustion and heat transfer enhancement, and the influence of inlet velocity, equivalent ratio, and materials on thermal performance was investigated. The results showed that pin fins embedding is beneficial to improving combustion, and the combustion efficiency of MCIPF and MCEPF reaches 98.5% and 98.7%, which is significantly higher than that of the conventional cylindrical combustor (MCC). However, with the increase of inlet velocity from 8 m/s to 14 m/s, MCIPF exhibits the highest external wall temperature with a range of (1302–1386 K), while MCEPF maintains the best temperature uniformity. As the inlet velocity increases to 10 m/s, the external wall temperature and temperature uniformity reach the optimum. Besides, under the conditions of different equivalence ratios, both external wall temperature and heat flux increases first and then decreases, meanwhile the temperature uniformity of MCEPF is significantly improved compared with that of MCIPF, they all exhibit the highest external wall temperature with an equivalence ratio of 1.1, and the thermal performance is greatly enhanced. By comparing the heat transfer performance of combustors with different materials based on MCEPF, it is interesting to find that the application of high thermal conductivity materials can not only increase the external wall temperature, but also improve the temperature uniformity. Therefore, materials with high thermal conductivity such as Aluminum, Red Copper and Silicon Carbide should be selected for application in micro combustors and their components. The current work provides a new design method for the enhanced heat transfer of the micro combustor.