基于压缩感知理论重构压电阻抗信号的钢结构损伤识别

基于压电阻抗(electromechanical impedance, EMI)技术,针对结构损伤识别提出了阻抗/导纳数据压缩与重构的方法,利用随机矩阵将监测系统中的原始阻抗数据向量进行线性映射,并将映射后的向量输入到接收系统中;基于压缩感知理论将重构原始数据的问题转化成非确定性多项式问题,并基于凸优化(convex optimization, CO)理论求解;在损伤识别阶段,利用均方根偏差(root mean square deviation, RMSD)统计指标对重构阻抗数据的识别效果进行评估,并与使用原始阻抗数据的效果进行对比。利用简支钢梁的局部损伤识别试验采集的阻抗数据证明所提出方法的有效性。结果表明：基于重构阻抗数据能够有效识别结构损伤,基系数矩阵的稀疏度随着测量数的减少而降低,一致球集合对应的稀疏度区间低于其他测量矩阵,阻抗数据重构效果随着压缩率的增加而减弱,当压缩率高于2.0时,部分使用重构阻抗数据识别结构损伤的误差将大于20%,损伤识别精度降低。     

盲重构频域阵列信号的压缩感知水声目标方位估计

针对复杂海洋环境条件下压缩感知水声目标方位估计性能下降的问题,利用盲源分离能够提高信噪比的优势,提出了一种盲重构频域阵列信号的压缩感知水声目标方位估计方法。首先将阵元域信号通过傅里叶变换方法得到多个子带阵列信号;然后对各个子带阵列信号进行复数域盲源分离得到子带解混矩阵和子带分离信号估计,并对子带分离信号进行属性分析和处理;再根据处理后的子带分离信号和子带解混矩阵重构子带阵列信号,对重构的子带阵列信号采用频域压缩感知方法进行空间谱估计,得到各个子带的空间谱;最后将各子带得到的空间谱进行求和,搜索求和后空间谱的峰值则可实现目标方位估计。模拟器数据和海上实测数据验证结果表明,同等条件下该方法的目标检测能力优于经典的最小方差无失真响应(Minimum Variance Distortionless Response,MVDR)方法、频域压缩感知(Compressed Sensing,CS)方法、盲源分离(Blind Source Separation,BSS)与MVDR相结合的方法(BSS+MVDR方法),测向精度更高,明显提高了弱目标信号的空间谱能量,增强了声呐检测弱目标的能力。     

频域单快拍压缩感知目标方位估计和信号恢复方法

方位估计和信号恢复分别是水下目标定位、跟踪和目标识别的前提。提出了一种阵列频域单快拍压缩感知的水下目标方位估计和信号恢复方法。首先将阵列接收数据变换到频域,取频域单快拍数据作为压缩感知的测量值,然后根据频域快拍对应的频率、搜索方位和阵列流形构造过完备的阵列流形矩阵作为压缩感知的感知矩阵,最后通过基追踪算法估计搜索方位上目标信号和功率,实现DOA估计与信号恢复。宽带仿真实验数据验证结果表明,同等条件下完成同样的目标方位分辨,提出的方法比最小方差无失真响应方法要求的阵元数和快拍数较少,要求的信噪比更低,恢复的目标信号更加准确,波形相关系数达到89%以上。海上实验数据处理结果表明,目标检测能力优于最小方差无失真响应方法,证明该方法可以适用于实际声呐系统。     

基于改进滑动窗口的渔船AIS轨迹数据压缩算法

为解决渔船自动识别系统(AIS)轨迹数据质量不高、渔船轨迹分析需要保留更多特征点的问题,提出了一种基于改进滑动窗口的渔船AIS轨迹数据压缩算法。结果表明:改进的算法利用相邻轨迹点间的经纬度变化趋势确定行驶特征点,在保留时序信息的同时压缩高密度的停滞点,并用采样法保留直行中间点,尽可能多地保留了轨迹特征点,实现了渔船轨迹的有效压缩;本研究中提出的基于改进滑动窗口的渔船AIS轨迹数据压缩算法与Douglas-Peucker算法相比,压缩率从99%降至94%以下,很好地保留了渔船轨迹特征点,同时也避免了Sliding Window轨迹压缩算法存在的轨迹形态失真问题,。研究表明,基于改进滑动窗口的渔船AIS轨迹数据压缩算法更适用于压缩渔船轨迹。     

基于区间编码的XML数据压缩方法

针对现有XML数据压缩方法在压缩数据上不支持有效连接操作问题,提出采用区间编码的压缩方法(region encodingbased XML data compression method,REXDC)对XML数据中的节点进行区间编码,实现结构连接;提出相同子树的概念和合并相同子树的方法,建立一种支持有效连接操作的存储模型,实现XML数据压缩,同时解决在压缩数据上不支持有效连接操作的问题;最后,以压缩率、压缩时间、解压时间及查询性能作为衡量标准,将REXDC与XGrind、XPress和XQzip算法进行比较。实验结果证明,REXDC具有较好的压缩性能和查询性能。     

基于EMD分解与压缩传感的泄漏电流压缩方法

为了提高绝缘子监测系统数据传输和处理速度,对非平稳泄漏电流信号进行数据压缩至关重要。压缩传感理论(Compressed Sensing,CS)将采样与压缩合并进行,少量采样就能很好地恢复信号,不仅降低对硬件要求,而且提高压缩效率。然而CS恢复非平稳信号过程中计算复杂度很高。提出经验模态分解(EMD)和CS相结合的方法,将非平稳泄漏电流分解成有限个相对平稳的固有模态IMF,然后对相对平稳的IMF分量进行CS处理。实验结果表明,CS处理经EMD分解的泄漏电流信号不仅提高整个系统的处理速度和运行效率,而且提高了压缩比和重构精度。     

智能交通系统在上海地铁的应用

智能交通系统(下简称ITS)是指采用现代通信技术、信息技术和计算机技术,将有关交通系统所涉及到的人、车、道及环境等有机地组合在一起,使其发挥智能作用,成为一个智能式系统,从而使交通系统达到安全、通     

智能交通系统控制技术在隧道设计中的应用

随着智能交通系统(ITS)技术的发展,将交通控制与诱导技术运用于工程设计,将有效缓解交通拥堵问题。结合龙耀路隧道设计,阐述了绿波控制方案和诱导技术的基本原理、流程和主要计算方法,提出了将交通控制中的绿波技术和ITS中的路线诱导技术更为广泛科学地应用到多个越江工程中,从系统层面提高越江工程的交通疏解效率。     

稀疏信号重构的罚函数神经网络模型

在压缩感知理论中,针对未知信号的稀疏性和信号非零元素位置的不确定性使得稀疏信号的重构比较困难,以及基于贪婪迭代方法的一系列匹配追踪算法和基于凸松弛方法的一系列基追踪算法对稀疏信号的重构概率不高,提出了一个罚函数神经网络模型。首先在感知矩阵A满足有限等距性质的前提下,压缩感知问题可以转化为等价的l_(1)-范数最小化问题。然后基于罚函数的思想构造能量函数,建立了解决稀疏信号重构的神经网络模型,并对其收敛性和优化能力进行了理论分析。仿真实验结果表明,当信号比较稀疏时,仅需较少的观测数,稀疏信号的重构概率就能接近100%。特别是在不同的观测数下,所提出的神经网络模型与正交匹配追踪算法、压缩采样匹配追踪算法及l_(1)-正则化最小二乘法相比,信号的重构概率分别平均提高了4.93、14.07、2.73个百分点。     

不停车收费技术及在上海虹桥国际机场出口收费站中的应用

1 概述 1.1 智能交通系统(ITS) 90年代以来,国际上将电子信息技术引入了道路运输系统,从而诞生了智能交通系统ITS(Intelligent Traffic svstem)。据专家估计,采用ITS,在今后20年内可降低8％的交通灾难,每年交通事故的死亡人数可减少30％～70％。据预测,到2012年,ITS技术可使交通堵塞减少20％。国外资料显示,采用ITS的建设费用,仅占道路基础设施建设费用的3％～4％,可见ITS不仅投资少,而且见效快。     

Fibre reinforced sands: Experiments and modelling

Sand reinforced with short polypropylene fibres has been tested in conventional triaxial compression and extension. The contribution of fibres to the strength was remarkable in compression while limited in extension confirming that it depends primarily on their orientation with respect to tensile strains. A modelling approach is proposed for coupling the effects of fibres with the stress–strain behaviour of unreinforced soil. It is necessary to define a fibre stiffness matrix and in this investigation it is assumed that fibres are working in their elastic domain. Any distribution of fibre orientations can be accounted for. The sand stiffness matrix is based on the Mohr Coulomb model although more elaborate models could be used. The constitutive model for the fibre-sand composite is calibrated against the results of drained triaxial compression and extension tests. Despite the simplistic nature of the Mohr-Coulomb assumptions for the sand matrix, simulations show how the influence of fibre orientation with respect to the strain conditions is captured and provide good agreement with experimental data.     

Deep learning for data anomaly detection and data compression of a long‐span suspension bridge

As intelligent sensing and sensor network systems have made progress and low‐cost online structural health monitoring has become possible and widely implemented, large quantities of highly heterogeneous data can be acquired during the monitoring. This has resulted in exceeding the capacity of traditional data analytics techniques, especially in monitoring large‐scale or critical civil structures. In particular, data storage has become a big challenge, hence, resulting in the emergence of data compression and reconstruction as a new area in structural health monitoring (SHM) of large infrastructure systems. SHM data generally include anomalies that can disturb structural analysis and assessment. The fundamental reasons for the abnormality of data are extremely complex. Therefore, reconstruction of the abnormal data is generally difficult and poses serious challenges to achieve high‐accuracy after data has been compressed. Considering these significant challenges, in this paper, a novel deep‐learning‐enabled data compression and reconstruction framework is proposed that can be divided into two phases: (a) a one‐dimensional Convolutional Neural Network (CNN) that extracts features directly from the input signals is designed to detect abnormal data with validated high accuracy; (b) a new SHM data compression and reconstruction method based on Autoencoder structure is further developed, which can recover the data with high‐accuracy under such a low compression ratio. To validate the proposed approach, acceleration data from the SHM system of a long‐span bridge in China are employed. In the abnormal data detection phase, the results show that the proposed method can detect anomaly with high accuracy. Subsequently, smaller reconstruction errors can be achieved even by using only 10% compression ratio for the normal data.     

Developing a Smart Structure Using Integrated Subspace‐Based Damage Detection and Semi‐Active Control

Damage detection in large building structures has always faced challenges due to analyzing the large amount of measured data. In this article, a new damage detection approach based on subspace method is proposed to identify damages using limited output data. Also, a new scheme is presented to develop a smart structure by integrating structural health monitoring with semi‐active control strategy. If damage occurs in such a structure under severe excitations, the proposed scheme has the capability to exert necessary control forces in order to compensate for damage and reduce simultaneously the dynamic response of the structure. The reliability and feasibility of the proposed method are demonstrated by implementing the technique to two shear building structures with semi‐active control devices. Results show that the damage could be identified accurately with saving time and cost due to less computation even under noise existence; and dynamic response is significantly reduced in the smart structure.     

On the prediction of effect of direction of welding on bead geometry and residual deformation of double-sided fillet welds

The present study describes how the effect of direction of welding is useful to minimize distortion in submerged arc welded double-sided fillet joints. In present work, angular distortion of 12 mm thick double-sided fillet welds was measured for same direction and reverse direction welding. It has been observed that the maximum magnitude of the angular distortion for reverse direction fillet welding is lower. Thermal history in horizontal and vertical plate of fillet welds was also measured for both same direction and reverse direction welding. After welding, the fillet welds were sectioned, polished and etched to measure the effect of direction of welding on weld bead geometry. To predict the temperature distribution and thermal history, a finite element (FE) elasto-plastic thermo-mechanical model has been developed for submerged arc welded double-sided fillet welds by using moving distributed heat source. The three-dimensional FE thermal model was verified by comparing peak temperature obtained with experimental values. The model results matched fairly well with experimental results with a variation of 6 percent for sample 1 and 7.5 percent for sample 2 for the maximum values of distortion, and a variation of 2-8 percent for peak temperatures in horizontal plate and 9 percent in web plate.     

考虑桩身非线性压缩的单桩沉降解析算法

桩顶沉降是桩基的主要控制参数。均质土和成层土中单桩桩顶沉降由桩端力引起的沉降、桩侧阻力引起的沉降和桩身压缩引起的沉降三部分组成。针对摩擦桩桩身压缩引起沉降的现有算法没有考虑到其非线性压缩,基于剪切位移法,考虑桩身非线性压缩,从理论上推导它的计算方法,进而得到单桩的沉降。经过对工程实例的计算与实测对比分析,证明了该方法具有较高的精度和可靠性,同时表明,桩身压缩引起的沉降占总沉降较大时,应考虑桩身的非线性压缩。最后对影响单桩沉降的因素进行分析,结果表明桩侧土破坏比、抗剪强度是影响单桩沉降的主要因素。     

Mix proportioning of underground cemented tailings backfill

The usage of cemented tailings backfill (cemented paste backfill) in the underground by mining industry is becoming increasingly important. However, until now, the mix proportioning of CTB has been mainly based on the realization of extensive laboratory tests on a large number of CTB mixes. Therefore, this paper presents a design method for mix proportioning of CTB to minimize the number of trial mixes and provide an appropriate mix proportion. This method is based on the pairing of the response surface method (RSM) and the desirability approach. First, the RSM was used to develop predictive models for the performance properties of CTB. The predicted properties in question are the uniaxial compression strength (UCS), the slump, the solid concentration (solid percent, %Solid) and the cost (based on cement cost) of the CTB. The predictive models that were developed were able to accurately represent the relationships between the physical and chemical characteristics of the CTB components (tailings, binder, water) and the above properties. The results of the modeling phase were then used as input data in the optimization phase (based on desirability approach) to develop optimal recipes for the studied CTBs. This study has demonstrated that the combination of the RSM and desirability approach represents an effective tool for CTB mix proportioning. It has also shown that the mix parameters (cement content, water-to-cement ratio, tailings fineness and density) affect the performance properties of CTB. The results of this research provide a more comprehensive engineering approach to CTB mix proportioning. The developed design method can be useful in reducing the laboratory test protocol needed for the determination of the optimal mix composition.     

A probabilistic fatigue strength model for brick masonry under compression

The paper presents the development of a model for the fatigue resistance of brick masonry under compression. The model takes into account the random nature of the fatigue strength phenomena and, as a consequence, proposes different model parameters as a function of the desired probability level. The model, based on a Weibull distribution, has been calibrated with the still limited experimental data on brick masonry under high cycle compression loading. Very good correlation is obtained. The results show that there is a clear trend of the experimental data to follow the Weibull distribution. It is also shown how the fatigue resistance of brick masonry is not only dependent on the magnitude of the stress cycles, but also on the magnitude of the minimum stress level. The paper also shows how the proposed model can be used in the reliability-based assessment of the fatigue performance of existing masonry arch bridges. Either the nominal probability of failure (reliability index) to fatigue or the remaining service life with a predefined probability level for an existing bridge can be predicted with the proposed method.     

Performance monitoring of low energy house,Macclesfield

A lot of work in the field of thermal modelling of buildings has been done using Fourier analysis by representing a set of data of time dependent variables by a Fourier Series. Major researchers have used a system of Continuous Fourier Transform, i.e. approximating a set of sampled data to be a continuous function which is periodic in nature but linear between two sampled instances and calculating the Fourier coefficients by using integral function and solving for six harmonics. This method, apart from being approximate, has mathematical limitations due to the presence of the integral. The calculations are complicated and time consuming. The approach of Discrete Fourier Transform, commonly used in digital signal processing, is introduced in this paper as a better alternative for solar thermal modelling, in that it provides a simpler approach, with as accurate results as the continuous method when six harmonics are considered and exact results at the sampled instances when Nyquist's criterion is met. This method takes only 1/120th of the computing time required for the continuous method.     

Recent advances on postbuckling analyses of thin-walled structures: Beams, frames and cylindrical shells

The lateral postbuckling response of thin-walled structures such as bars and frames with members having steel rolled shapes as well as circular cylindrical shells under axial compression is thoroughly reconsidered. More specifically via a simple and very efficient technique it is found that beams with rolled shapes (symmetric or non symmetric) under uniform bending and axial compression exhibit a stable lateral-torsional secondary path with limited margins of postbuckling strength. New findings for the static and dynamic stability of frames with crooked steel members-due to the presence of residual stresses-are also reported. It is comprehensively established that the coupling effect due to initial crookedness and loading eccentricity may have a beneficial effect on the load-carrying capacity of the frames. Moreover, simple mechanical models are proposed for simulating the buckling mechanism of axially compressed circular cylindrical shells. Very recently Bodner and Rubin proposed an 1-DOF mechanical model whose buckling parameters correlated to those of the shells by using an empirical formula based on experimentally observed shell buckling loads. In the present analysis a new 2-DOF model for the static and dynamic buckling of axially compressed circular cylindrical shells, which can include mode coupling, is presented.