The millennium development goals: strategic implications for the Latin American and Caribbean statistical systems

Includes bibliography

Good practices in monitoring and reporting on the Millennium Development Goals: National lessons from Latin America

Includes bibliography

Vibration and oil analysis for monitoring problems related to water contamination in rolling

Trying to reduce particle contamination in lubrication systems, industries of the whole world spend millions of dollars each year on the improvement of filtration technology. In this context, by controlling fluid cleanliness, some companies are able to reduce failures rates up to 85 percent. However, in some industries and environments, water is a contaminant more frequently encountered than solid particles, and it is often seen as the primary cause of component failure. Only one percent of water in oil is enough to reduce life expectancy of a journal bearing by 80 percent. For rolling bearing elements, the situation is worse because water destroys the oil film and, under the extreme temperatures and pressures generated in the load zone of a rolling bearing element, free and emulsified water can result in instantaneous flash-vaporization giving origin to erosive wear. This work studies the effect of water as lubricant contaminant in ball bearings, which simulates a situation that could actually occur in real systems. In a designed bench test, three basic lubricants of different viscosities were contaminated with different contents of water. The results regarding oil and vibration analysis are presented for different bearing speeds.

Adaptive filter feature identification for structural health monitoring in aeronautical panel

This paper presents an approach for structural health monitoring (SHM) by using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage to use a RLS filter is the clear possibility to perform an online SHM procedure since that the identification is also valid for non-stationary linear systems. An online damage-sensitive index feature is computed based on autoregressive (AR) portion of coefficients normalized by the square root of the sum of the square of them. The proposed method is then utilized in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. A hypothesis test employing the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize the damages simulated in the structure. The results have shown the applicability and drawbacks the method and the paper concludes with suggestions to improve it. ©2010 Society for Experimental Mechanics Inc.

Specialist tool for monitoring the measurement degradation process of induction active energy meters

This paper presents a methodology and a specialist tool for failure probability analysis of induction type watt-hour meters, considering the main variables related to their measurement degradation processes. The database of the metering park of a distribution company, named Elektro Electricity and Services Co., was used for determining the most relevant variables and to feed the data in the software. The modeling developed to calculate the watt-hour meters probability of failure was implemented in a tool through a user friendly platform, written in Delphi language. Among the main features of this tool are: analysis of probability of failure by risk range; geographical localization of the meters in the metering park, and automatic sampling of induction type watt-hour meters, based on a risk classification expert system, in order to obtain information to aid the management of these meters. The main goals of the specialist tool are following and managing the measurement degradation, maintenance and replacement processes for induction watt-hour meters. © 2011 IEEE.

Versatile and easy-to-assemble measurement system for impedance-based structural health monitoring

In this paper we present a versatile and easy-to-assemble measurement system for structural health monitoring (SHM) based on the electromechanical impedance (EMI) technique. The hardware of the proposed system consists only of a common data acquisition (DAQ) device with external resistors and allows real-time data acquisition from multiple sensors. Besides the low-cost compared to conventional impedance analyzers, the hardware and the software are simple and easier to implement than other measurement systems that have been recently proposed.

Structural Health Monitoring based on AR models and PZT sensors

This paper presents a new approach for damage detection in Structural Health Monitoring (SHM) systems, which is based on the Electromechanical Impedance (EMI) principle and Autoregressive (AR) models. Typical applications of EMI in SHM are based on computing the Frequency Response Function (FRF). In this work the procedure is based on the EMI principle but the results are determined through the coefficients of AR models, which are computed from the time response of PZT transducers bonded to the monitored structure, and acting as actuator and sensors at the same time. The procedure is based on exciting the PZT transducers using a wide band chirp signal and getting its time response. The AR models are obtained in both healthy and damaged conditions and used to compute statistics indexes. Practical tests were carried out in an aluminum plate and the results have demonstrated the effectiveness of the proposed method. © 2012 IEEE.

Monitoring in precision metal drilling process using multi-sensors and neural network

This paper presents a new method to estimate hole diameters and surface roughness in precision drilling processes, using coupons taken from a sandwich plate composed of a titanium alloy plate (Ti6Al4V) glued onto an aluminum alloy plate (AA 2024T3). The proposed method uses signals acquired during the cutting process by a multisensor system installed on the machine tool. These signals are mathematically treated and then used as input for an artificial neural network. After training, the neural network system is qualified to estimate the surface roughness and hole diameter based on the signals and cutting process parameters. To evaluate the system, the estimated data were compared with experimental measurements and the errors were calculated. The results proved the efficiency of the proposed method, which yielded very low or even negligible errors of the tolerances used in most industrial drilling processes. This pioneering method opens up a new field of research, showing a promising potential for development and application as an alternative monitoring method for drilling processes. © 2012 Springer-Verlag London Limited.

A system for environmental monitoring of hydroelectric reservoirs in Brazil

Environmental monitoring of aquatic systems is an important tool to support policy makers and environmental managers' decisions. Long-term, continuous collection of environmental data is fundamental to the understanding of an aquatic system. This paper aims to present the integrated system for environmental monitoring (SIMA), a long-term temporal series system with a web-based archive for limnological and meteorological data. The following environmental parameters are measured by SIMA: chlorophyll-a (µgL-1), water surface temperature (ºC), water column temperature by a thermistor string (ºC), turbidity (NTU), pH, dissolved oxygen concentration (mg L-1), electric conductivity (µS cm-1), wind speed (ms-1) and direction (º), relative humidity (%), shortwave radiation (Wm-2) and barometric pressure (hPa). The data were collected in a preprogrammed time interval (1 hour) and were transmitted by satellite in quasi-real time for any user within 2500 km of the acquisition point. So far, 11 hydroelectric reservoirs are being monitored with the SIMA buoy. Basic statistics (mean and standard deviation) and an example of the temporal series of some parameters were displayed at a database with web access. However, sensor and satellite problems occurred due to the high data acquisition frequency. Sensors problems occurred due to the environmental characteristics of each aquatic system. Water quality sensors rapidly degrade in acidic waters, rendering the collected data invalid. Data is also rendered invalid when sensors become infested with periphyton. Problems occur with the satellites' reception of system data when satellites pass over the buoy antenna. However, the data transfer at some inland locations was not completed due to the satellite constellation position. Nevertheless, the integrated system of water quality and meteorological parameters is an important tool in understanding the aquatic system dynamic. It can also be used to create hydrodynamics models of the aquatic system to allow for the study of meteorological implications to the water body.

An Experimental Study on the Effect of Temperature on Piezoelectric Sensors for Impedance-Based Structural Health Monitoring

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of uremic solutes on reactive oxygen species in vitro model systems as a possibility of support the renal function management

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Design and implementation of wireless sensor networks for impedance-based structural health monitoring using ZigBee and Global System for Mobile Communications

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Piezoelectric transducers assessed by the pencil lead break for impedance-based structural health monitoring

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

New approach for power transformer protection based on intelligent hybrid systems

A power transformer needs continuous monitoring and fast protection as it is a very expensive piece of equipment and an essential element in an electrical power system. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can mislead the conventional protection affecting the power system stability negatively. This study proposes the development of a new algorithm to improve the protection performance by using fuzzy logic, artificial neural networks and genetic algorithms. An electrical power system was modelled using Alternative Transients Program software to obtain the operational conditions and fault situations needed to test the algorithm developed, as well as a commercial differential relay. Results show improved reliability, as well as a fast response of the proposed technique when compared with conventional ones.