Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

Equivalent Carbon Dioxide Capture and Storage Processes in Offshore Petroleum Production Facilities

The present study approaches the economic and technical evaluation of equivalent carbon dioxide (CO(2) eqv.) capture and storage processes, considered in a proposal case compared to a base case. The base case considers an offshore petroleum production facility, with high CO(2) content (4 vol%) in the composition of the produced gas and both CO(2) and natural gas emissions to the atmosphere, called CO(2) eqv. emissions. The results obtained with this study, by using a Hysys process simulator, showed a CO(2) emission reduction of 65% comparing the proposal case in relation to the base case.

Knowledge transfer in product development processes: A case study in small and medium enterprises (SMEs) of the metal-mechanic sector from Sao Paulo, Brazil

This paper reports a research that evaluated the product development methodologies used in Brazilian small and medium-sized metal-mechanic enterprises (SMEs), in a specific region of Sao Paulo. The tool used for collecting the data was a questionnaire, which was developed and applied through interviews conducted by the researchers in 32 companies. The main focus of this paper can be condensed in the synthesis-question ""Is only the company responsible for the development?"" which was analyzed thoroughly. The results obtained from this analysis were evaluated directly (through the respective percentages of answers) and statistically (through the search of an index which demonstrates if two questions are related). The results point to a degree of maturity in SMEs, which allows product development to be conducted in cooperation networks. (C) 2007 Elsevier Ltd. All rights reserved.

Assembling a consistent set of sentences in relational probabilistic logic with stochastic independence

We examine the representation of judgements of stochastic independence in probabilistic logics. We focus on a relational logic where (i) judgements of stochastic independence are encoded by directed acyclic graphs, and (ii) probabilistic assessments are flexible in the sense that they are not required to specify a single probability measure. We discuss issues of knowledge representation and inference that arise from our particular combination of graphs, stochastic independence, logical formulas and probabilistic assessments. (C) 2007 Elsevier B.V. All rights reserved.

MODELLING AND CONTROL OF ERSW PROCESSES BY NEURONAL NETWORK

A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.

Microstructure and texture assessment of Al-Mn-Fe-Si (3003) aluminum alloy produced by continuous and semicontinuous casting processes

Aluminum sheets are currently produced by the direct-chill process (DC). The need for low-cost aluminum sheets is a challenge for the development of new materials produced by the twin roll caster (TRC) process. It is expected that sheets produced from these different casting procedures will differ in their microstructure. These differences in microstructure and in the crystallographic texture have great impact on sheet mechanical properties and formability. The present study investigated microstructure and evaluated texture of two strips of Al-Mn-Fe-Si (3003) aluminum alloy produced by TRC and by hot-rolling processes. It was possible to notice that the microstructure, morphology, and grain size of the TRC sample were more homogenous than those found in hot-rolled samples. Both strips, obtained by the two processes, showed strong texture gradient across the thickness.

Mechanical Blocking Mechanism for the Columnar to Equiaxed Transition

Mechanical blocking of the columnar front during the columnar to equiaxed transition (CET) is studied by quantitatively comparing the CET positions obtained with one stochastic model and two deterministic models for the unidirectional solidification of an Al-7 (wt pct) Si alloy. One of the deterministic models is based on the solutal blocking of the columnar front, whereas the other model is based on the mechanical blocking. The solutal-blocking model and the mechanical-blocking model with the traditional blocking fraction of 0.49 give columnar zones larger than those predicted with the stochastic model. When a blocking fraction of 0.2 is adopted, however, the agreement is very good for a range of nucleation undercoolings and number density of equiaxed grains. Therefore, changing the mechanical-blocking fraction in deterministic models from 0.49 to 0.2 seems to model more accurately the mechanical-blocking process that can lead to the CET.

Degradation of Poly(ethylene glycol) in Aqueous Solution by Photo-Fenton and H(2)O(2)/UV Processes

This article reports experimental results obtained in a laboratory-scale photochemical reactor on the photodegradation of poly(ethylene glycol) (PEG) in aqueous solutions by means of the photo-Fenton and H(2)O(2)/UV processes. Dilute water solutions of PEG were fed to a batch reactor, mixed with pertinent reactants, and allowed to react under different conditions. Reaction progress was evaluated by sampling and analyzing the concentration of the total organic carbon (TOC) in solution as a function of the reaction time. Organic acids formed during oxidation were determined by HPLC analyses. The main acids detected in both processes were acetic and formic. Glycolic acid was detected only in the photo-Fenton process, and malonic acid was detected only in the H(2)O(2)/UV treatment, indicating that different reaction paths occur in these processes. The characteristics of both processes are discussed, based on the evolution of the TOC-time curves and the concentration profiles of the monitored organic acids. The experimental results constitute a contribution to the design of industrial processes for the treatment of wastewaters containing soluble polymers with similar properties.

Treatment of Aqueous Effluents Containing Phenol by the O(3), O(3)-UV, and O(3)-H(2)O(2) Processes: Experimental Study and Neural Network Modeling

In this work, the oxidation of the model pollutant phenol has been studied by means of the O(3), O(3)-UV, and O(3)-H(2)O(2) processes. Experiments were carried out in a fed-batch system to investigate the effects of initial dissolved organic carbon concentration, initial, ozone concentration in the gas phase, the presence or absence of UVC radiation, and initial hydrogen peroxide concentration. Experimental results were used in the modeling of the degradation processes by neural networks in order to simulate DOC-time profiles and evaluate the relative importance of process variables.

Investigation of the mass transfer processes during the desalination of water containing phenol and sodium chloride by electrodialysis

Oxidation processes are used in wastewater treatment when conventional processes are not effective due to the presence of recalcitrant organic contaminants, like phenol. However, the presence of ionic compounds associated with organic pollutants may retard the oxidation. In this work the transport of species contained in an aqueous solution of phenol containing sodium chloride was evaluated in an electrodialysis (ED) system. An experimental study was carried out in which the influence of the process variables on the phenol loss and sodium chloride removal was investigated. Experiments were also performed without current, in order to determine the phenol transfer due to diffusion. The phenol and salt concentration variations in the ED compartments were measured over time, using dedicated procedures and an experimental design to determine the global characteristic parameters. A phenomenological approach was used to relate the phenol, salt and water fluxes with the driving forces (concentration and electric potential gradients). Under ED conditions, two contributions were pointed out for the phenol transport, i.e. diffusion and convection, this latter coming from the water flux due to electroosmosis related to the migration of salts. The fitting of the parameters of the transport equations resulted in good agreement with the experimental results over the range of conditions investigated. (c) 2008 Elsevier B.V. All rights reserved.

USE OF SOLAR ENERGY IN THE TREATMENT OF WATER CONTAMINATED WITH PHENOL BY PHOTOCHEMICAL PROCESSES

The solar driven photo-Fenton process for treating water containing phenol as a contaminant has been evaluated by means of pilot-scale experiments with a parabolic trough solar reactor (PTR). The effects of Fe(II) (0.04-1.0 mmol L(-1)), H(2)O(2) (7-270 mmol L(-1)), initial phenol concentration (100 and 500 mg C L(-1)), solar radiation, and operation mode (batch and fed-batch) on the process efficiency were investigated. More than 90% of the dissolved organic carbon (DOC) was removed within 3 hours of irradiation or less, a performance equivalent to that of artificially-irradiated reactors, indicating that solar light can be used either as an effective complementary or as an alternative source of photons for the photo-Fenton degradation process. A non-linear multivariable model based on a neural network was fit to the experimental results of batch-mode experiments in order to evaluate the relative importance of the process variables considered on the DOC removal over the reaction time. This included solar radiation, which is not a controlled variable. The observed behavior of the system in batch-mode was compared with fed-batch experiments carried out under similar conditions. The main contribution of the study consists of the results from experiments under different conditions and the discussion of the system behavior. Both constitute important information for the design and scale-up of solar radiation-based photodegradation processes.

Minimizing total tardiness in a stochastic single machine scheduling problem using approximate dynamic programming

This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.

Stochastic stability analysis for the constant-modulus algorithm

We derive an easy-to-compute approximate bound for the range of step-sizes for which the constant-modulus algorithm (CMA) will remain stable if initialized close to a minimum of the CM cost function. Our model highlights the influence, of the signal constellation used in the transmission system: for smaller variation in the modulus of the transmitted symbols, the algorithm will be more robust, and the steady-state misadjustment will be smaller. The theoretical results are validated through several simulations, for long and short filters and channels.

The Policy Iteration Algorithm for Average Continuous Control of Piecewise Deterministic Markov Processes

The main goal of this paper is to apply the so-called policy iteration algorithm (PIA) for the long run average continuous control problem of piecewise deterministic Markov processes (PDMP`s) taking values in a general Borel space and with compact action space depending on the state variable. In order to do that we first derive some important properties for a pseudo-Poisson equation associated to the problem. In the sequence it is shown that the convergence of the PIA to a solution satisfying the optimality equation holds under some classical hypotheses and that this optimal solution yields to an optimal control strategy for the average control problem for the continuous-time PDMP in a feedback form.

THE VANISHING DISCOUNT APPROACH FOR THE AVERAGE CONTINUOUS CONTROL OF PIECEWISE DETERMINISTIC MARKOV PROCESSES

This work is concerned with the existence of an optimal control strategy for the long-run average continuous control problem of piecewise-deterministic Markov processes (PDMPs). In Costa and Dufour (2008), sufficient conditions were derived to ensure the existence of an optimal control by using the vanishing discount approach. These conditions were mainly expressed in terms of the relative difference of the alpha-discount value functions. The main goal of this paper is to derive tractable conditions directly related to the primitive data of the PDMP to ensure the existence of an optimal control. The present work can be seen as a continuation of the results derived in Costa and Dufour (2008). Our main assumptions are written in terms of some integro-differential inequalities related to the so-called expected growth condition, and geometric convergence of the post-jump location kernel associated to the PDMP. An example based on the capacity expansion problem is presented, illustrating the possible applications of the results developed in the paper.