滨海基岩矿床安全开采合理隔离层厚度的确定

针对滨海基岩矿床安全开采合理隔离层厚度留设问题，基于材料力学、结构力学等共七种理论计算方法综合确定隔离层厚度，利用点柱式上向水平分层充填法建立三维数值计算模型，通过结合FLAC3D数值模拟软件，分析理论计算结果的合理性，研究不同中段开采充填情况下第四系底部的稳定性特征，最终得出安全开采所需的隔离层厚度必须在12m以上，合理的开采上限必须在-57m以上。通过分析数值计算模型第四系底部的沉降变形，发现第四系底部最大沉降集中于中间采场 ，最大沉降量为13.73mm。研究成果为滨海基岩矿床安全开采，提高资源回采率提供了有益指导。     

Hybrid fully convolutional networks-based skin lesion segmentation and melanoma detection using deep feature

Fully convolutional networks (FCNs) take the input of arbitrary size and produce correspondingly sized output with efficient inference and learning. The automatic diagnosis of melanoma is very essential for reducing the mortality rate by identifying the disease in earlier stages. A two-stage framework is used for implementing the melanoma detection, segmentation of skin lesion, and identification of melanoma lesions. Two FCNs based on VGG-16 and GoogLeNet are incorporated for improving the segmentation accuracy. A hybrid framework is used for incorporating these two FCNs. The classification is done by extracting the feature from segmented lesion by using deep residual network and a hand-crafted feature. Classification is done by support vector machine. The performance analysis of our framework gives a promising accuracy, that is, 0.8892 for classification in ISBI 2016 dataset and 0.853 for ISIC 2017 dataset.     

一种相位测试用曲口面天线的设计与应用

相位测试技术可满足不同外形天线罩的在线测试需求。通过数值仿真,设计最佳变换曲线完成矩形 传输波导与圆形辐射天线的拟合连接,能够有效降低天线驻波比,实现测试探头的高增益收发,提升测试有效性。 在维持驻波比参数前提下,对天线口面弧线给予二次曲率调整,可以适应不同外形天线罩的测试稳定性要求。根据 仿真结果加工的低驻波比反射相位测试天线,已应用于多个型号天线罩成型中的相位在线测试,提高了监控的有效 性,验证了设计仿真结果的正确性。     

Effect of Reynolds number and boundary layer thickness on the performance of V-cone flowmeter using CFD

The effect of Reynolds number and boundary layer thickness on the performance of V-cone flowmeter has been evaluated using computational fluid dynamics (CFD). The shear stress transport k-ω (SST k-ω) turbulence model has been adopted for closure. The performance of two V-cone flowmeters with different beta ratios (β) viz., 0.6 and 0.7 for a fixed vertex angle (ϕ) of 60° has been analysed as a function of Reynolds number (Re). The results show that the coefficient of discharge (C_d) increases with Reynolds number in the laminar and transition flow regimes whereas it is nearly constant in turbulent flow regime. From the results, it can be concluded that C_d is independent of Re for values equal to 4000 and beyond. Further, it is also seen that the performance of the V-cone flowmeter is not affected by the upstream boundary layer thickness if the velocity profiles having different boundary layer thickness are extracted from an axial distance of 10D and more are fed at 5D upstream of the meter. However, the meter is sensitive to the extracted velocity profile from an axial distance of 5D and uniform velocity profile being fed at 5D upstream. The value of C_d may be sensitive as a result of the pressure variation due to the obstruction.     

黄河万家寨河段河冰冰厚遥感提取及年内变化特征分析

冰凌观测是防凌的前提,是冰凌研究的基础,因此全面准确的冰凌观测可为科学防凌提供可靠的依据。为此,以黄河万家寨库区河段为例,通过冰厚反演算法对其冰厚数据进行遥感反演,利用Lebedev模型对反演结果进行验证,并对结果进行年内变化特征分析。结果表明,卫星遥感反演结果与实测及模型验证结果接近,相关系数为0.8;冰厚演变总体呈成冰、流凌、初封、稳封、融冰、开河的生消演变过程。反演冰厚结果可为黄河内蒙段防凌减灾等实际工作提供参考依据。     

基于残差决策的自动飞行控制系统远程实时故障诊断

针对自动飞行控制系统结构复杂、关联部件众多,发生故障时诊断时间长,从而影响飞机运行效率的问题,提出一种基于飞机通信寻址报告系统(ACARS)的远程实时故障诊断方案。首先,分析自动飞行控制系统的故障特点,设计搭建检测滤波器;然后,利用ACARS数据链实时发送的自动飞行控制系统的关键信息进行相关部件的残差计算,并根据残差决策算法进行故障诊断及定位;最后,针对不同故障部件残差间的差异大、决策门限无法统一的缺点,提出基于二次差值的残差决策改进算法,减缓了检测对象的整体变化趋势,降低了随机噪声和干扰的影响,避免了将瞬态故障诊断为系统故障的情况。实验仿真结果表明,基于二次差值的改进残差决策算法避免了多决策门限的复杂性,在采样时间为0.1 s的情况下,故障检测所需时间大约为2 s,故障检测时间大幅降低,有效故障检测率大于90%。     

可控中子孔隙度测井仪器设计

源距与屏蔽体厚度是直接影响可控中子孔隙度测井仪器测量准确性的重要参数。源距不仅影响测井仪器的测量误差，还影响测井仪器对地层孔隙度的灵敏度。屏蔽体厚度是保障测井响应完全反映地层的重要参数。从灵敏度、屏蔽率以及误差3个方面确定可控中子孔隙度测井仪器的源距与屏蔽体厚度。研究结果表明:近探测器源距越小，测井仪器灵敏度越高；近远探测器的间距对测量误差的影响随间距的增大，先减小再增大；当屏蔽率在70%以上且屏蔽率随厚度的变化较为缓慢时的屏蔽体厚度可作为屏蔽体最低厚度。     

焊后低温热处理对马氏体不锈钢组织和性能的影响

对ZG06Cr13Ni4Mo马氏体不锈钢进行了焊后低温热处理工艺试验(240、300 ℃),通过显微组织分析、拉伸及弯曲试验、硬度试验及残余应力测试对不同低温热处理下焊接接头的显微组织、力学性能、硬度和残余应力等进行了研究。结果表明,经低温热处理后,接头焊缝热影响区组织为回火马氏体及碳化物,接头焊缝区的组织为低碳马氏体+块状马氏体+碳化物,接头的抗拉强度变化不大,硬度略有下降,经240 ℃低温热处理后,焊接接头焊缝处的残余应力消除了69.1%。     

No-reference quality assessment of dynamic sports videos based on a spatiotemporal motion model

This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.