Approach and structure of stabilizing control system preventing an extension of synchronism loss

Recently, large-capacity power stations have been built far from load centers with long-distance transmission lines. Therefore, if a fault occurs at the line, generators in the large-capacity power station may lose synchronism from the remaining generators [1, 3]. To prevent an extension of loss of synchronism to other generators, fast shedding of some generators is an effective measure. The following methods have been proposed so far: A method [3] based on energy function approach; and a method [2] which estimates and predicts the relative swing among generators using data measured on-line at each generator and proposes shedding some generators for stabilization. This method requires a large communication network for an exchange of data between power stations. This paper presents a new stabilizing method and a newly developed stabilizing control system which does not require a large communication network because it utilizes generator output, voltage and current measured on-line in the vicinity of the large-capacity power station. Using these measured data, the system estimates and predicts the relative swing between generators in the large-capacity power station and the remaining generators. Finally, the number of generators to be shed for stabilization is decided and shedding is performed. Configuration and characteristics of the developed stabilizing control system are shown. The validity of this method is confirmed by simulation and testing using an artificial power system.     

Adaptive histogram-based filter for image restoration

A novel filter for image restoration is proposed in this paper. The filter estimates histogram of original image via input image. It gets a membership function through the histogram, and the membership function contains a lot of information of original image. Then a weighted fuzzy mean filter is established based on this membership function; meanwhile, the filter adaptively adopts different filter scale according to the character divergence of image region and intensity of impulsive noise. Experimental result shows that new filter gives superior performance to conventional filters and currently used fuzzy filter.     

火电厂灰水回收处理远程监控系统设计

火电厂灰水回收处理远程监控系统由PLC控制器、现场操作站、上位监控计算机及工业以太网构成。系统采用光纤通信和基于工业以太网的信息传送,将基于PLC的工业自动控制和视频监控及防火防盗监控有机的结合起来,实现了灰水回收处理设备的远程自动控制及工业处理过程综合监视。     

Influence of concrete composition on the characterization of fracture surface

An experimental method based on laser triangulation was used to measure the 3-D profile of fracture surface of concrete. The projective-covering method was established to determine the fractal characteristics of fracture surface. Based on the experiment, the influence of composition of concrete on the fractal dimension, including water–binder ratio, maximum aggregate size and aggregate type, was investigated. The variation of fractal dimension with the material composition was also analysed to make further understanding of fracture mechanism of concrete.     

On probabilistic fatigue models for composite materials

The general purpose of this article is to review the main ideas in fatigue analysis of composites in the context of the application of probabilistic methods, both theoretical and computational. That is why most deterministic concepts of composite materials fatigue are summarized together with stochastic approaches. The application of the perturbation based Stochastic Finite Element Method (SFEM) to fatigue analysis of homogeneous and heterogeneous media is shown. Further, homogenization method in its effective modules approach is proposed below for application in fatigue processes modeling of linear elastic periodic random composites. Considering stochastic character of the analysis, the reliability tools appropriate to multicomponent materials are presented together with the specially adopted brittle and ductile fracture criteria.     

Shear testing of thick adhesive layers using the ENF-specimen

An existing experimental method to determine cohesive laws for adhesive layers loaded in shear is further developed. The method is based on differentiation of the energy release rate (ERR) with respect to the adhesive shear deformation at the crack tip. The test geometry used is an ENF-specimen for which the adherends are assumed to deform linearly elastic. The original method is expanded to account for situations where the thickness of the adhesive layer is not negligible as compared to the adherend thickness. To this end, a novel mathematical expression for the energy release rate (ERR) is derived. No assumptions on the form of the cohesive law are made; it is implicitly included in the derivation. The expression for the ERR contains the applied load and the shear deformation of the adhesive layer at the initial position of the crack tip, in addition to geometrical properties and the elastic modulus of the adherend material. Numerical simulations are performed to verify the accuracy of the mathematical expression for the ERR. Preliminary results from experiments performed on an epoxy adhesive are presented. The cohesive law of the adhesive layer is extracted by using a blunted crack tip. Verifying simulations confirm that the local pre-fracture behavior is accurately captured.     

Agent-based monitoring service for management of disruptive events in supply chains

Schedules of supply chains are generated with buffers to absorb the effect of disruptive events that could occur during their execution. Schedules can be systematically repaired through specific modifications within buffers by using appropriate decision models that consider the distributed nature of a supply chain. To this aim, information of disruptive events at occurrence or in advance allows decision models to make better decisions. To detect and predict disruptive events along a schedule execution, a service-oriented monitoring subsystem that uses a reference model for defining monitoring models was proposed. This subsystem offers services for collecting execution data of a schedule and environment data, and assessing them to detect/anticipate disruptive events. Because of the distributed nature and the complexity of these services functionalities, this paper presents an agent-based approach for their implementation. This technology allows dealing with supply chain monitoring by structuring monitoring subsystem functionalities as a set of autonomous entities. These entities are able to perform tailored plans created at execution time to concurrently monitor different schedules. A case study is described to try out the implemented prototype system.     

Robot Cloud: Bridging the power of robotics and cloud computing

Cloud computing is shaping the cyber world and evolves as a key computing and service platform for sharing resources including platforms, software applications and everything in the form of services. This is known “X as a Service”. Although it brings our age unparalleled computing ability and economic benefits, the application of cloud computing is still limited currently in the cyberspace due to the cloud services can only reside in cloud instead of our daily life environment. In fact, there are still a plethora of physical position based on-site service demands that cloud computing could help little due to the “cyber limitation”. In this paper, we aim to integrate the cyber world and the physical world by bringing up the idea of “Robot Cloud” to bridge the power of robotics and cloud computing. To make it possible, we design a novel Robot Cloud stack to support our idea and adopt the service-oriented architecture (SOA) to make the functional modules in the Robot Cloud more flexible, extensible and reusable. Then we develop a prototype of Robot Cloud using the popular Google App Engine to demonstrate our design method. Finally, we conduct the simulation experiments with a “robot show” application scenario to evaluate our scheduling policy and identify the effect of different request distributions and robot center solutions.     

面向家庭服务的人体动作识别

为了提高家庭服务机器人的智能,提出了一种面向家庭服务的人体动作识别算法。首先,提出了利用运动历史图像自适应更新背景的方法,对家庭环境进行背景建模;然后,利用YCbCr图像与灰度图像二值化的综合消除阴影,从而实现人体分割与定位;最后,提出了基于高熵变化量的时空特征方法,并结合环境信息对人体进行动作识别。实验结果表明,提出的背景模型能较好的克服暂时停止运动的物体被背景吸收的问题,并能有效地对背景的纯净度进行评价,同时,根据提出的动作识别机制,结合家庭环境的布置知识总体识别率可以达到95%。基本可以满足机器人家庭服务的要求。     

Distributed video coding based on vector quantization: Application to capsule endoscopy

We present in this paper a new distributed video coding (DVC) architecture for wireless capsule endoscopy. It is based on the state of the art DVC systems, but without using key frames. Instead, it uses an adapted vector quantization (VQ) with a searching complexity that is shifted to the decoder. VQ allows creating a good side information (SI) by exploiting the similarities in human anatomy. Thus, SI is created from a codebook (CB) rather than by motion compensated prediction. This approach decreases largely the complexity of the encoder, which codes only Wyner-Ziv frames, and allows a progressive decoding. The encoder of the proposed DVC generates only a simple hash that is used by the decoder to select the corresponding VQ codeword. The obtained experimental results show that rate-distortion results are better than those of JPEG, and show the possibility of using scalable coding to control the used rate and energy.