A Smart Deep Convolutional Neural Network for Real-Time Surface Inspection

A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products, largely used in many industrial sectors. However, computers used in the production line of small to medium size companies, in general, lack performance to attend real-time inspection with high processing demands. In this paper, a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed. The architecture is based on the state-of-the-art SqueezeNet approach, which was originally developed for usage with autonomous vehicles. The main features of the proposed model are: small size and low computational burden. The model is 10 to 20 times smaller when compared to other networks designed for the same task, and more than 700 times smaller than general networks. Also, the number of floating-point operations for a prediction is about 50 times lower than the ones used for similar tasks. Despite its small size, the proposed model achieved near-perfect accuracy on a public dataset of 1800 images of six types of steel rolling defects.     

κ-Opioid Signaling in the Lateral Hypothalamic Area Modulates Nicotine-Induced Negative Energy Balance

Several studies have reported that nicotine, the main bioactive component of tobacco, exerts a marked negative energy balance. Apart from its anorectic action, nicotine also modulates energy expenditure, by regulating brown adipose tissue (BAT) thermogenesis and white adipose tissue (WAT) browning. These effects are mainly controlled at the central level by modulation of hypothalamic neuropeptide systems and energy sensors, such as AMP-activated protein kinase (AMPK). In this study, we aimed to investigate the kappa opioid receptor (κOR)/dynorphin signaling in the modulation of nicotine’s effects on energy balance. We found that body weight loss after nicotine treatment is associated with a down-regulation of the κOR endogenous ligand dynorphin precursor and with a marked reduction in κOR signaling and the p70 S6 kinase/ribosomal protein S6 (S6K/rpS6) pathway in the lateral hypothalamic area (LHA). The inhibition of these pathways by nicotine was completely blunted in κOR deficient mice, after central pharmacological blockade of κOR, and in rodents where κOR was genetically knocked down specifically in the LHA. Moreover, κOR-mediated nicotine effects on body weight do not depend on orexin. These data unravel a new central regulatory pathway modulating nicotine’s effects on energy balance.     

铌对取向硅钢冷轧组织织构的影响

采用光学显微镜(OM)、电子背散射衍射(EBSD)等研究了铌对取向硅钢冷轧过程中的组织与织构的影响。结果表明:含铌正火板和不含铌正火板经冷轧后都是条带状组织,但含铌冷轧板在宽度方向更窄。铌元素的存在对织构也具有优化作用,经过中间退火后,含铌冷轧板二次冷轧织构得到明显改善,相较于不含铌二次冷轧板拥有强度较低的旋转立方织构以及强度较高的{111}<112>织构,其取向密度最高可达12.460。     

基于改进奇异值分解滤波和谱峭度的滚动轴承故障诊断

针对含噪信号的有效奇异值个数难以确定的问题，提出了一种改进的奇异值分解降噪方法--奇异值累积法。该方法通过计算奇异值的实际下降值与奇异值平均下降速度累积量的差值，并取该差值最大值点的位置作为有效奇异值的分界点来确定有效奇异值的个数。在此基础上，提出了一种基于奇异值累积法与快速谱峭度的滚动轴承故障诊断方法。采用奇异值累积法对原信号进行降噪处理，然后利用快速谱峭度确定滤波器中心频率及带宽，通过分析频段包络谱中明显的频率成分来诊断故障。该方法可以有效去除信号中的噪声，使得到的峭度值所反映的故障冲击更接近实际情况。对含内圈、外圈故障的滚动轴承实验数据进行分析，实验结果表明，相比快速谱峭度的故障诊断方法，该方法具有更好的故障识别效果。     

整体壁板离散填料滚弯成形有限元模拟

具有一定曲率外形的铝合金整体壁板属于典型的多筋零部件,传统弯曲成形工艺成形困难,容易产生多种缺陷。提出了离散填料辅助滚弯成形整体2A12T4铝合金壁板滚弯工艺,并通过实验与整体填料滚变成形进行了对比,同时采用有限元模拟技术,探究了离散填料辅助整体壁板滚弯成形中的影响因素。研究结果表明:填料数量、上下垫板厚度等因素对成形性能影响较大,填料在3~6块时成形稳定,可以有效地避免筋条屈曲与失稳;随垫板厚度增加,壁板表面圆弧更加光滑、连续,但是回弹性增强;上下垫板分别在10~20 mm厚度时,综合性能较好。通过离散填料辅助滚弯技术可以成形出质量较高的整体壁板。     

轧机垂直系统动力学参数辨识

 针对轧机垂直系统动力学参数可信度不足等问题，提出一种基于实测数据的改进粒子群算法辨识轧机垂直系统动力学参数的方法。首先,将轧机垂直系统刚度和阻尼考虑成达芬振子和范德波尔振子，构建轧机垂直系统非线性动力学模型，并对粒子群算法进行改进；然后，通过数值仿真算例辨识得到系统在感染噪声和不含噪声时的动力学参数，验证了该算法的有效性；最后，以现场某轧机垂直系统为研究对象，基于现场实测数据，应用该算法进行辨识，得到了轧机垂直系统动力学参数估计，通过实测位移、速度和加速度信号分别与辨识后的位移、速度和加速度信号进行对比，证明该方法辨识轧机垂直系统动力学参数结果可靠，具有一定的工程应用价值。     

轧机两侧刚度差的数字化分析与改善措施

轧机两侧刚度差是轧机功能精度的最重要指标之一，以弹跳方程为基础定量计算了轧机两侧刚度差对轧制稳定性的影响，主要包括调平值、调平值随轧制力的变化以及甩尾3个方面。以此为基础在某热轧线建立了轧机刚度评价体系，对轧机功能精度进行管控。同时，还分析了轧机两侧刚度差的影响因素，并在定量分析的基础上采取了一系列的改善措施，包括衬板、垫片维护、最大压靠轧制力和标定轧制力的调整等，使轧机刚度和轧制稳定性得到大幅提升。     

Excellent Energy Storage and Charge-discharge Performances in PbHfO3 Antiferroelectric Ceramics

Single phase PbHfO₃ antiferroelectric ceramics were prepared via rolling process. It is revealed that the rolling process can reduce the grain size and increase the bulk density, which lead to the enhanced breakdown strength up to 268 kV/cm versus 219 kV/cm of samples using the conventional solid-state method. As a result, high recoverable energy density of 7.6 J/cm³ with an efficiency of 80.8 % was achieved. Meanwhile, a large current density of 1381 A/cm² and an ultrahigh peak power density up to 170 MW/cm³ were observed under 250 kV/cm. In addition, unique electrical polarization response characteristics at different electric fields and temperature-induced structural phase transitions were also investigated. The energy storage performance and charge-discharge properties of PbHfO₃ were first studied in this communication and all the results indicate that PbHfO₃ ceramic is a promising candidate for pulse power applications.     

Fabrication of composites from different carbon content ferrous powders adopting thermomechanical processes

In this research, deep consolidation technique is utilized for processing of low and high carbon content ferrous powders to manufacture composite material. High carbon content ferrous powders were used as reinforcing material. The powder particles were allowed to mix with low carbon content ferrous powders in 50:50 weight percent for fabrication of composites. The composites were heat treated at three different temperatures (i.e., 800°C, 900°C, and 1000°C). The changes in microstructure, microhardness, the grain size, and bonding among powder particles were studied. Refinement of grains was observed and this led to improved hardness enabling the processed material to be used as a suitable composite. Abrasive wear tests were carried out using a laboratory tribometer in dry reciprocating sliding contact against Sic abrasive paper. The outcomes demonstrate that the abrasive wear resistance was notably affected by the treatment temperature and hardness of the composites.