Structural health monitoring system based on multi-agent coordination and fusion for large structure

In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.     

Looking ahead: Joint small group detection and tracking in crowd scenes

Small group detection and tracking in crowd scenes are basis for high level crowd analysis tasks. However, it suffers from the ambiguities in generating proper groups and in handling dynamic changes of group configurations. In this paper, we propose a novel delay decision-making based method for addressing the above problems, motivated by the idea that these ambiguities can be solved using rich temporal context. Specifically, given individual detections, small group hypotheses are generated. Then candidate group hypotheses across consecutive frames and their potential associations are built in a tree. By seeking for the best non-conflicting subset from the hypothesis tree, small groups are determined and simultaneously their trajectories are got. So this framework is called joint detection and tracking. This joint framework reduces the ambiguities in small group decision and tracking by looking ahead for several frames. However, it results in the unmanageable solution space because the number of track hypotheses grows exponentially over time. To solve this problem, effective pruning strategies are developed, which can keep the solution space manageable and also improve the credibility of small groups. Experiments on public datasets demonstrate the effectiveness of our method. The method achieves the state-of-the-art performance even in noisy crowd scenes.     

Models for circular data from time series spectra

Circular data are those for which the natural support is the unit circle and its toroidal extensions. Numerous constructions have been proposed which can be used to generate models for such data. We propose a new, very general, one based on the normalization of the spectra of complex-valued stationary processes. As illustrations of the new construction's application, we study models for univariate circular data obtained from the spectra of autoregressive moving average models and relate them to existing models in the literature. We also propose and investigate multivariate circular models obtained from the high-order spectra of stationary stochastic processes generated using linear filtering with an autoregressive moving average response function. A new family of distributions for a Markov process on the circle is also introduced. Results for asymptotically optimal inference for dependent observations on the circle are presented which provide a new paradigm for inference with circular models. The application of one of the new families of spectra-generated models is illustrated in an analysis of wind direction data.     

Influence of protein and lipid concentration of the test lubricant on the wear of ultra high molecular weight polyethylene

To gain a better understanding of the ultra-high molecular weight polyethylene (UHMWPE) wear mechanism in the physiological environment, the effects of protein and lipid constituents of synovial fluid on the specific wear rate of UHMWPE were examined experimentally. The multidirectional sliding pin-on-plate wear tester was employed to simulate the simplified sliding condition of hip joint prostheses. Bovine serum γ-globulin and synthetic l--DPPC were used as model protein and lipid constituents of synovia, respectively. Results of the wear test indicated that the UHMWPE wear rate primarily depended on the protein concentration of the test lubricant. Lipids acted as a boundary lubricant and reduced polyethylene wear in the low protein lubricants. However, the polyethylene wear rate increased with increasing lipid concentrations if the protein concentration was within the physiological level. Increased interactions between protein and lipid molecules and lipid diffusion to polyethylene surface might be responsible for the increased wear.     

Emergency department status boards: user-evolved artefacts for inter- and intra-group coordination

Large, easily viewed status boards are commonly used in some healthcare settings such as emergency departments, operating theaters, intensive care units, and inpatient wards. Because these artefacts were developed by front-line users, and have little to no supervisory or regulatory control, they offer valuable insights into the theories of work and hazard held by those users. Although the status boards case were locally developed over many years for within-group coordination, they have also become useful for between-group coordination across organizational boundaries. In this paper, we compare and contrast the use of such status boards in two disparate settings: a US emergency department, and a UK pediatric ward, and note striking similarities in their form and usage, despite the large differences in setting.     

节理岩体的边界元模型及其应用

边界元法广泛应用于岩石力学问题的最大障碍是岩体的非均质及其包含的大量节理断层，本文采用多子域思想结合节理断层的非线性模型较好地解决了这一难题。该法在老厂锡矿的应用较好地解释了该矿采场顶板的冒落机理。     

浅谈赣抚大堤樟防1标射水造墙的接缝技术和处理措施

介绍射水造墙的接缝原理，并把自己在施工过程中为确保接缝质量达到设计要求而总结出一些经验和处理措施提出为一起探讨。     

正交试验在摩擦焊工艺参数优化中的应用

通过正交试验得出摩擦焊工艺参数中对接头抗拉强度的影响的顺序是摩擦压力、顶锻压力、摩擦时间。为在生产实际中制定摩擦焊接工艺规范提供了重要的参考依据。     

适于复杂信息融合系统的近似联合概率数据关联算法

文中在B.Zhou提出的直接概率计算(DC)和近似概率计算(AC)算法基础上提出了一种新的近似多传感器多目标联合概率数据关联算法。近似概率法是以一个目标为中心的近似聚为构造互联事件的起点，并在计算中将DC和AC结合得到的一种全邻的点迹—航迹关联算法，它能有效地提高目标点迹—航迹的关联正确率，在计算时耗上较完全联合概率法快得多，能满足工程中实时性的要求。将其在杂波下目标密集、航迹复杂的数据融合系统中进行实验，对关联正确率，关联耗时等与最近邻法进行了比较，效果较好。     

太阳电池板结构应力-应变状态分析

多层胶接是太阳电池板的结构特点,由于不同材料的弹性模量、热膨胀系数和泊松比不同,在温度场 作用下会产生热应力应变,在多次热交变过程中热应力．应变累积最后导致结构层间剥离,因此研究温度场作用 下太阳电池板结构应力应变状态具有非常重要的实际意义。本文推导了模拟太阳电池板结构应力-应变状态的一 维模型,该模型同样适用于分析多层胶接结构应力应变状态。