Damage detection in beams from modal and wavelet analysis using a stationary roving mass and noise estimation

This paper uses the Continuous Wavelet Transform Analysis on mode shapes for damage identification. The wavelet analysis is applied to the difference in the mode shapes between a healthy and a damaged state. The paper also includes a novel methodology for estimating the level of noise of the experimental mode shapes based on a standard Signal to Noise Ratio (SNR). The estimated SNRs are used for identifying and making emphasis on the less noisy data. Moreover, a mass attached to the structure is considered to enhance the sensitivity of the structure to damage. Modal analysis is performed for different positions of the mass along the beam. The results obtained for all the positions of the mass are combined so an averaging process is implicitly applied. The paper presents the results from an experimental test of a cantilever steel beam with different severity levels of damage at the same location. The results show that the use of the attached mass reduces the effect of noise and increases the sensitivity to damage. Little damage can be identified with the proposed methodology even using a small number of sensors and only the first five bending modes.     

DR机房建设与验收监测的要点探讨

随着我国放射诊断学的快速发展,当前许多医院都在购置或使用医用数字化X射线摄影系统(DR)机房建设必须符合国家标准满足临床使用。本文结合日常工作中总结的经验,从DR机房的规划设计、放射防护设施施工、放射防护验收监测方面探讨了DR机房建设过程中的要点,为医院的机房建设提供参考。     

高校实验室计算机网络故障诊断技术研究

为了提升高校实验数据处理水平,高校实验室的相关建设工作已经步入正轨,但层出不穷的信息安全问题也向高校实验室计算机网络维护工作提出了新的挑战。文章从现阶段高校实验室计算机网络的相关建设工作出发,简要论述引发网络故障的具体原因,并对其诊断技术进行探讨。     

An improved damage diagnostic technique based on Singular Spectrum Analysis and time series models

An approach to enhance the sensitivity of the damage index using the prediction errors of autoregressive – autoregressive exogenous models by augmenting Singular Spectrum Analysis (SSA) to detect and locate minor damage is presented. Numerical simulation studies are carried out by considering a simply supported beam with single and multiple cracks. An experimental study on a reinforced cement concrete beam has been carried out to validate the technique using different levels of damage. The studies emphasise that the SSA improves the sensitivity of the damage index for detection and also localisation, handling environmental/operational variability and measurement noise.     

基于视频分析的南水北调跨渠桥危化车预警系统

跨渠桥梁是南水北调中线工程的重要基础设施,危化品运输车辆一旦在跨渠桥梁上发生事故,不仅会对桥体结构造成很大损坏,还会对沿线水质产生较大污染。如果能及时发现,提前预警,就可以针对每座桥梁的情况提早防范,快速处理,将损失降到最低。针对以上需求建立基于智能视频分析的危化品车辆流量、类别监控识别与统计分析系统,采用智能监控和态势感知等建立了多层次、全方位预警决策和风险管控平台。平台功能涉及车辆流量、类别识别、统计分析技术和预警功能,能辨识经过跨渠桥梁的车辆,特别是能对危化品运输车辆出入桥梁的信息进行记录和流量统计,对车辆偏离车道、异常停车、翻车、冲入渠道等异常事件能第一时间进行信息报告与自动预警。该项目已付诸实施,为南水北调跨渠桥梁安全管控提供了新的技术防护手段。     

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%。     

龙滩坝8#采场地压监测与结果分析

为掌握龙滩坝8#采场矿体在开采过程中地压的变化规律，在结合现场实际情况的同时，根据开挖揭露的地质条件，采用钻孔应力计、锚杆应力计、收敛计、多点位移计和声发射对采场矿柱、顶板及巷道变形情况进行监测，得到回采过程中矿柱、顶板、巷道的受力状况。掌握采场地压的变化规律，为矿体的开采设计提供参考。     

大柳塔煤矿五盘区5-2煤层DDF2断层特征

大柳塔煤矿五盘区5-2煤层在三维地震资料解释中发现存在一条影响较大、伸展较远的断层（DDF2断层）横切5-2煤层。综合研究表明，DDF2断层为走向为东南—西北方向（111°～291°）、倾向为西南方向（201°）的高角度正断层。该断层为坳陷盆地形成后控制部分煤层沉积:在D306钻孔和D307钻孔所在区域形成时间较早，形成于5-2煤层沉积之后，结束于4-3煤层形成之后，控制5-2煤与4-3煤之间的地层沉积，为同沉积断层；该断层在D304钻孔和D305钻孔所在区域形成时间较晚，形成于4-2煤层沉积之后，结束于3-1煤层形成之后，局部控制4-2煤层与3-1煤层之间沉积，为准同生沉积断层。DDF2断层形成于东南方向，逐渐向西北方向迁移、加剧到最后尖灭。     

改进ILoG算子的故障检测方法

针对强背景噪声干扰下轮对轴承故障特征微弱、难以准确检测的问题,提出了一种自适应改进高斯拉普拉斯(improved Laplacian of Gaussian,简称ILoG)算子的微弱故障检测方法。ILoG算子滤波器具有优良的信号突变特征检测能力,将其用于轮对轴承故障信号的冲击特征检测,同时利用水循环算法(water cycle algorithm,简称WCA)的寻优特性,并行搜寻筛选最佳的ILoG算子影响参数,通过对参数优化后ILoG算子滤波后信号做进一步包络解调分析,提取出轮对轴承微弱的故障特征信息。对实际轮对轴承外圈和内圈故障信号分析的结果表明,该方法可以有效检测出轴承微弱故障特征频率,故障检测效果优于小波阈值和多尺度形态学差值滤波方法。     

Photomemory and Pulse Monitoring Featured Solution-Processed Near-Infrared Graphene/Organic Phototransistor with Detectivity of 2.4 × 1013 Jones

Emerging graphene/organic phototransistors are eye-catching technologies owing to their unique merits including easy/low-cost fabrication, temperature independent, and achieving various functions. However, their development in the near-infrared (NIR) region is experiencing a bottleneck of inferior sensitivity due to low exciton dissociation efficiency and inefficient charge extraction rate. Here, a novel-design solution-processed graphene/organic NIR phototransistor is reported, that is, creatively introducing electron extraction layer of ZnO on graphene channel and employing organic ternary bulk heterojunction as photosensitive layer, successfully breaking that bottleneck. The phototransistor exhibits a high responsivity of 6.1 × 10⁶ A W⁻¹, a superior detectivity of 2.4 × 10¹³ Jones, and a remarkable minimum detection power of 1.75 nW cm⁻² under 850 nm radiation. Considering its excellent NIR detection performance, a noncontact transmission-type pulse monitoring is carried out with no external circuit support, from which human pulse signal and heart rate can be displayed in real time. The phototransistor, interestingly, can be switched into a photomemory function with a retention time of 1000 s in the atmosphere through a gate voltage of −20 V. The design takes the characteristics of graphene/organic phototransistors to a higher level, beyond the limit of sensitivity, and opens up a novel approach for developing multifunction devices.