Hardware and software architecture for power quality analysis

This paper presents a novel concept for power quality hardware and software architecture. Software tools related to detection, classification and characterization of power quality events can be integrated into a Distribution Control Center in which the interconnection between different subsystems is being carried out through the Internet allowing flexibility to the system. This system is implemented using wavelet analysis applied in all proposed algorithms. Different power quality events are taken as examples to illustrate the capabilities of the proposed method. The obtained results reveal that the proposed architecture is feasible to be implemented as an integral part of a control center system.The proposed system has the property of fast and accurate detection and classification of any power quality disturbance event and introduces a new PQ index determination that allows characterizing any type of disturbance including the non-periodic signals.     

Data mining of resilience indicators

In recent years, the Asia-Pacific region has experienced several financial setbacks, including speculative attacks in 1998 and the SARS outbreak in 2003. Financial stresses of this nature are unanticipated, and not all of the dangers can be predicted by the examination of market information and macroeconomic indicators. The Early Warning System (EWS) that has been adopted by the International Monetary Fund may not be able to predict future financial crises for all possible scenarios, because shocks come in many different forms. To supplement the EWS, this paper proposes a data mining framework to measure the resilience of an economy. The resilience framework does not predict a crisis, but rather assesses the current state of health of an economy and its ability to withstand a financial shock should one occur. The framework is based on a feedback system consisting of two stages. The first stage assigns a resilience score to each economy based on a fuzzy logic scoring scheme that is built on the ambiguous reasoning of experts. The second stage uses the classification tree approach to estimate thresholds for each economic indicator, and examines the quality of the fuzzy score. The result from the second stage is then passed back to the first stage as feedback. The final result is obtained when the feedback system reaches its equilibrium state. The proposed resilience framework is applied to the external-sector and the public-sector economies of several countries to illustrate its applicability.     

Extensions of LDA by PCA mixture model and class-wise features

Linear discriminant analysis (LDA) is a data discrimination technique that seeks transformation to maximize the ratio of the between-class scatter and the within-class scatter. While it has been successfully applied to several applications, it has two limitations, both concerning the underfitting problem. First, it fails to discriminate data with complex distributions since all data in each class are assumed to be distributed in the Gaussian manner. Second, it can lose class-wise information, since it produces only one transformation over the entire range of classes. We propose three extensions of LDA to overcome the above problems. The first extension overcomes the first problem by modelling the within-class scatter using a PCA mixture model that can represent more complex distribution. The second extension overcomes the second problem by taking different transformation for each class in order to provide class-wise features. The third extension combines these two modifications by representing each class in terms of the PCA mixture model and taking different transformation for each mixture component. It is shown that all our proposed extensions of LDA outperform LDA concerning classification errors for synthetic data classification, hand-written digit recognition, and alphabet recognition.     

A tolerant approach to reconstruct topology from unorganized trimmed surfaces

Presented in this paper is a topology reconstruction algorithm from a set of unorganized trimmed surfaces. Error-prone small geometric elements are handled to give proper topological information. It gives complete topology to topologically complete models, and it is also tolerant to incomplete models. The proposed algorithm is vertex-based in that clues for topological information are searched from the set of vertices first, not from that of edges.     

Hydrogenated amorphous silicon thin-film transistor arrays fabricated by digital lithography

A jet-printed digital-lithographic method, in place of conventional photolithography, was used to fabricate 64 /spl times/ 64 pixel (300 /spl mu/m pitch) matrix addressing thin-film transistor (TFT) arrays. The average hydrogenated amorphous silicon TFT device within an array had a threshold voltage of /spl sim/3.5 V, carrier mobility of 0.7 cm/sup 2//V/spl middot/s, subthreshold slope of 0.76 V/decade, and an on/off ratio of 10/sup 8/.     

Pile Response Adjacent to Braced Excavation

The excavation of soil for the construction of basements or cut-and-cover tunnels results in ground movements. One particular concern is that the excavation-induced lateral soil movements may adversely affect any nearby pile foundation. The lateral loads imposed by the soil movements induce bending moments and deflections in the pile, which may lead to structural distress and failure. This paper presents the results of an actual full-scale instrumented study that was carried to examine the behavior of an existing pile due to nearby excavation activities resulting from the construction of a 16 m deep cut-and-cover tunnel. The pile was located 3 m behind a 0.8 m thick diaphragm wall. Excavation to the formation level that was 16 m below the ground surface resulted in a maximum lateral pile movement of 28 mm. A simplified numerical procedure based on the finite-element method was used to analyze the pile response. Generally, the theoretical predictions were in reasonable agreement with the measured results.     

Data fitting with a spline using a real-coded genetic algorithm

To obtain a good approximation for data fitting with a spline, frequently we have to deal with knots as variables. The problem to be solved then becomes a continuous nonlinear and multivariate optimization problem with many local optima. Therefore, it is difficult to obtain the global optimum. In this paper, we propose a method for solving this problem by using a real-coded genetic algorithm. Our method can treat not only data with a smooth underlying function, but also data with an underlying function having discontinuous points and/or cusps. We search for the best model among candidate models by using the Bayes Information Criterion (BIC). With this, we can appropriately determine the number and locations of knots automatically and simultaneously. Five examples of data fitting are given to show the performance of our method.     

An integrated modelling environment for the embodiment of mechanical systems

The efficient, economical and often elegant transformation from a design schema to an embodied design solution containing real components is essential for the commercial success of a product. More often the ability of the designer to explore an optimum solution is severely frustrated by the analytically intensive and time-consuming aspects of embodying a concept. This paper presents a computer based system-modelling tool that is to be used by designers during the transformation of a concept to an embodied solution particularly to deal with standard components. This environment provides for the representation of conceptual schemas and subsequent embodiment from computer based component selection modules. These selection modules encompass the full range of electronic representations for standard mechanical components. The strategy for representing a mechanical system, its included components and their associated representations is discussed. The process of constructing a system model, specifying the desired performance characteristics and system resolution are also described.     

Controlling mechanical systems with backlash—a survey

Backlash is one of the most important non-linearities that limit the performance of speed and position control in industrial, robotics, automotive, automation and other applications. The control of systems with backlash has been the subject of study since the 1940s. This survey reveals that surprisingly few control innovations have been presented since the early path breaking papers that introduced the describing function analysis of systems with backlash. Promising developments are however taking place using adaptive and non-linear control strategies.