873 resultados para Wide area networks (Computer networks)
Resumo:
A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.
Resumo:
This paper discusses a proposed new communications framework for phasor measurement units (PMU) optimized for use on wide area networks. Traditional PMU telecoms have been optimized for use in environments where bandwidth is restricted. The new method takes the reliability of the telecommunications medium into account and provides guaranteed delivery of data whilst optimizing for realtime delivery of the most current data. Other important aspects, such as security, are also considered.
Resumo:
The integration of an ever growing proportion of large scale distributed renewable generation has increased the probability of maloperation of the traditional RoCoF and vector shift relays. With reduced inertia due to non-synchronous penetration in a power grid, system wide disturbances have forced the utility industry to design advanced protection schemes to prevent system degradation and avoid cascading outages leading to widespread blackouts. This paper explores a novel adaptive nonlinear approach applied to islanding detection, based on wide area phase angle measurements. This is challenging, since the voltage phase angles from different locations exhibit not only strong nonlinear but also time-varying characteristics. The adaptive nonlinear technique, called moving window kernel principal component analysis is proposed to model the time-varying and nonlinear trends in the voltage phase angle data. The effectiveness of the technique is exemplified using both DigSilent simulated cases and real test cases recorded from the Great Britain and Ireland power systems by the OpenPMU project.
Resumo:
Resource monitoring in distributed systems is required to understand the 'health' of the overall system and to help identify particular problems, such as dysfunctional hardware or faulty system or application software. Monitoring systems such as GridRM provide the ability to connect to any number of different types of monitoring agents and provide different views of the system, based on a client's particular preferences. Web 2.0 technologies, and in particular 'mashups', are emerging as a promising technique for rapidly constructing rich user interfaces, that combine and present data in intuitive ways. This paper describes a Web 2.0 user interface that was created to expose resource data harvested by the GridRM resource monitoring system.
Resumo:
In a distributed environment remote entities, usually the producers or consumers of services, need a means to publish their existence so that clients, needing their services, can search and find the appropriate ones that they can then interact with directly. The publication of information is via a registry service, and the interaction is via a high-level messaging service. Typically, separate libraries provide these two services. Tycho is an implementation of a wide-area asynchronous messaging framework with an integrated distributed registry. This will free developers from the need to assemble their applications from a range of potentially diverse middleware offerings, which should simplify and speed application development and more importantly allow developers to concentrate on their own domain of expertise. In the first part of the paper we outline our motivation for producing Tycho and then review a number of registry and messaging systems popular with the Grid community. In the second part of the paper we describe the architecture and implementation of Tycho. In the third part of the paper we present and discuss various performance tests that were undertaken to compare Tycho with alternative similar systems. Finally, we summarise and conclude the paper and outline future work.
Resumo:
This paper presents a video surveillance framework that robustly and efficiently detects abandoned objects in surveillance scenes. The framework is based on a novel threat assessment algorithm which combines the concept of ownership with automatic understanding of social relations in order to infer abandonment of objects. Implementation is achieved through development of a logic-based inference engine based on Prolog. Threat detection performance is conducted by testing against a range of datasets describing realistic situations and demonstrates a reduction in the number of false alarms generated. The proposed system represents the approach employed in the EU SUBITO project (Surveillance of Unattended Baggage and the Identification and Tracking of the Owner).
Resumo:
In the last years the number of industrial applications for Augmented Reality (AR) and Virtual Reality (VR) environments has significantly increased. Optical tracking systems are an important component of AR/VR environments. In this work, a low cost optical tracking system with adequate attributes for professional use is proposed. The system works in infrared spectral region to reduce optical noise. A highspeed camera, equipped with daylight blocking filter and infrared flash strobes, transfers uncompressed grayscale images to a regular PC, where image pre-processing software and the PTrack tracking algorithm recognize a set of retro-reflective markers and extract its 3D position and orientation. Included in this work is a comprehensive research on image pre-processing and tracking algorithms. A testbed was built to perform accuracy and precision tests. Results show that the system reaches accuracy and precision levels slightly worse than but still comparable to professional systems. Due to its modularity, the system can be expanded by using several one-camera tracking modules linked by a sensor fusion algorithm, in order to obtain a larger working range. A setup with two modules was built and tested, resulting in performance similar to the stand-alone configuration.
Resumo:
This work presents a method to estimate and correct slow time-dependent position errors due to non perfect ground station synchronization and tropospheric propagation. It uses opportunity traffic emissions, i.e. signals transmitted from the aircrafts within the coverage zone. This method is used to overcome the difficulty of installing reference beacons simultaneously visible by all the base stations in a given Wide Area Multilateration (WAM) system.
Resumo:
Mode of access: Internet.
Resumo:
Human motion monitoring is an important function in numerous applications. In this dissertation, two systems for monitoring motions of multiple human targets in wide-area indoor environments are discussed, both of which use radio frequency (RF) signals to detect, localize, and classify different types of human motion. In the first system, a coherent monostatic multiple-input multiple-output (MIMO) array is used, and a joint spatial-temporal adaptive processing method is developed to resolve micro-Doppler signatures at each location in a wide-area for motion mapping. The downranges are obtained by estimating time-delays from the targets, and the crossranges are obtained by coherently filtering array spatial signals. Motion classification is then applied to each target based on micro-Doppler analysis. In the second system, multiple noncoherent multistatic transmitters (Tx's) and receivers (Rx's) are distributed in a wide-area, and motion mapping is achieved by noncoherently combining bistatic range profiles from multiple Tx-Rx pairs. Also, motion classification is applied to each target by noncoherently combining bistatic micro-Doppler signatures from multiple Tx-Rx pairs. For both systems, simulation and real data results are shown to demonstrate the ability of the proposed methods for monitoring patient repositioning activities for pressure ulcer prevention.