Detection of faults in a high speed packaging machine using a multilayer perceptron (MLP)

In high speed manufacturing systems, continuous operation is desirable, with minimal disruption for repairs and service. An intelligent diagnostic monitoring system, designed to detect developing faults before catastrophic failure, or prior to undesirable reduction in output quality, is a good means of achieving this. Artificial neural networks have already been found to be of value in fault diagnosis of machinery. The aim here is to provide a system capable of detecting a number of faults, in order that maintenance can be scheduled in advance of sudden failure, and to reduce the necessity to replace parts at intervals based on mean time between failures. Instead, parts will need to be replaced only when necessary. Analysis of control information in the form of position error data from two servomotors is described.

A fast two-grid and finite section method for a class of integral equations on the real line with application to an acoustic scattering problem in the half-plane

We consider the numerical treatment of second kind integral equations on the real line of the form ∅(s) = ∫_(-∞)^(+∞)▒〖κ(s-t)z(t)ϕ(t)dt,s=R〗 (abbreviated ϕ= ψ+K_z ϕ) in which K ϵ L_1 (R), z ϵ L_∞ (R) and ψ ϵ BC(R), the space of bounded continuous functions on R, are assumed known and ϕ ϵ BC(R) is to be determined. We first derive sharp error estimates for the finite section approximation (reducing the range of integration to [-A, A]) via bounds on (1-K_z )^(-1)as an operator on spaces of weighted continuous functions. Numerical solution by a simple discrete collocation method on a uniform grid on R is then analysed: in the case when z is compactly supported this leads to a coefficient matrix which allows a rapid matrix-vector multiply via the FFT. To utilise this possibility we propose a modified two-grid iteration, a feature of which is that the coarse grid matrix is approximated by a banded matrix, and analyse convergence and computational cost. In cases where z is not compactly supported a combined finite section and two-grid algorithm can be applied and we extend the analysis to this case. As an application we consider acoustic scattering in the half-plane with a Robin or impedance boundary condition which we formulate as a boundary integral equation of the class studied. Our final result is that if z (related to the boundary impedance in the application) takes values in an appropriate compact subset Q of the complex plane, then the difference between ϕ(s)and its finite section approximation computed numerically using the iterative scheme proposed is ≤C_1 [kh log⁡〖(1⁄kh)+(1-Θ)^((-1)⁄2) (kA)^((-1)⁄2) 〗 ] in the interval [-ΘA,ΘA](Θ<1) for kh sufficiently small, where k is the wavenumber and h the grid spacing. Moreover this numerical approximation can be computed in ≤C_2 N log⁡N operations, where N = 2A/h is the number of degrees of freedom. The values of the constants C1 and C2 depend only on the set Q and not on the wavenumber k or the support of z.

Acoustic scattering by an inhomogeneous layer on a rigid plate

The problem of scattering of time-harmonic acoustic waves by an inhomogeneous fluid layer on a rigid plate in R2 is considered. The density is assumed to be unity in the media: within the layer the sound speed is assumed to be an arbitrary bounded measurable function. The problem is modelled by the reduced wave equation with variable wavenumber in the layer and a Neumann condition on the plate. To formulate the problem and prove uniqueness of solution a radiation condition appropriate for scattering by infinite rough surfaces is introduced, a generalization of the Rayleigh expansion condition for diffraction gratings. With the help of the radiation condition the problem is reformulated as a system of two second kind integral equations over the layer and the plate. Under additional assumptions on the wavenumber in the layer, uniqueness of solution is proved and the nonexistence of guided wave solutions of the homogeneous problem established. General results on the solvability of systems of integral equations on unbounded domains are used to establish existence and continuous dependence in a weighted norm of the solution on the given data.

Bounding the role of black carbon in the climate system: a scientific assessment

Black carbon aerosol plays a unique and important role in Earth’s climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg yr�-1 in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W m�-2 with 90% uncertainty bounds of (+0.08, +1.27)Wm�-2. Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W m�-2. Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W m�-2 with 90% uncertainty bounds of +0.17 to +2.1 W m�-2. Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W m�-2, is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (�-0.50 to +1.08) W m-�2 during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (�-0.06 W m�-2 with 90% uncertainty bounds of �-1.45 to +1.29 W m�-2). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.

The impact of cognitive control on children's goal monitoring in a time-based prospective memory task

The present study investigated whether developmental changes in cognitive control may underlie improvements of time-based prospective memory. Five-, 7-, 9-, and 11-year-olds (N = 166) completed a driving simulation task (ongoing task) in which they had to refuel their vehicle at specific points in time (PM task). The availability of cognitive control resources was experimentally manipulated by imposing a secondary task that required divided attention. Children completed the driving simulation task both in a full attention condition and a divided attention condition where they had to carry out a secondary task. Results revealed that older children performed better than younger children on the ongoing task and PM task. Children performed worse on the ongoing and PM tasks in the divided attention condition compared to the full attention condition. With respect to time monitoring in the final interval prior to the PM target, divided attention interacted with age such that older children’s time monitoring was more negatively affected by the secondary task compared to younger children. Results are discussed in terms of developmental shifts from reactive to proactive monitoring strategies.

Cities reducing their greenhouse gas emissions

The study asks how well are cities doing in reducing their greenhouse gas emissions. Data from six cities with repeat GHG emission inventories for the period 2004–2009 is examined: Berlin, Boston, Greater Toronto, London, New York City and Seattle. All of the cities are reducing their per capita GHG emissions, primarily through changes to stationary combustion. On average the cities are reducing per capita emissions by 0.27 t CO2e/capita per year; this is about the same average rate as the cities nation states, although the cities are reducing emissions faster in percentage terms.

Vehicular particulate matter emissions in road tunnels in Sao Paulo, Brazil

In the metropolitan area of Sao Paulo, Brazil, ozone and particulate matter ( PM) are the air pollutants that pose the greatest threat to air quality, since the PM and the ozone precursors ( nitrogen oxides and volatile organic compounds) are the main source of air pollution from vehicular emissions. Vehicular emissions can be measured inside road tunnels, and those measurements can provide information about emission factors of in-use vehicles. Emission factors are used to estimate vehicular emissions and are described as the amount of species emitted per vehicle distance driven or per volume of fuel consumed. This study presents emission factor data for fine particles, coarse particles, inhalable particulate matter and black carbon, as well as size distribution data for inhalable particulate matter, as measured in March and May of 2004, respectively, in the Janio Quadros and Maria Maluf road tunnels, both located in Sao Paulo. The Janio Quadros tunnel carries mainly light-duty vehicles, whereas the Maria Maluf tunnel carries light-duty and heavy-duty vehicles. In the Janio Quadros tunnel, the estimated light-duty vehicle emission factors for the trace elements copper and bromine were 261 and 220 mu g km(-1), respectively, and 16, 197, 127 and 92 mg km(-1), respectively, for black carbon, inhalable particulate matter, coarse particles and fine particles. The mean contribution of heavy-duty vehicles to the emissions of black carbon, inhalable particulate matter, coarse particles and fine particles was, respectively 29, 4, 6 and 6 times higher than that of light-duty vehicles. The inhalable particulate matter emission factor for heavy-duty vehicles was 1.2 times higher than that found during dynamometer testing. In general, the particle emissions in Sao Paulo tunnels are higher than those found in other cities of the world.

Evaluation of a Micro PV-Diesel Hybrid System in Tanzania

In April 2011 a monitoring system was installed to enable studies of the performance and the usage of a micro PV-Diesel Hybrid system at the Ihushi Development Center (IDC) near Mwanza in Tanzania. Estimations of the load have been obtained by a survey of installed appliances and interviews with users of installed equipment. The load profile obtained by measurements has been analyzed and compared to estimations of the energy use. Further, the system size and performance were studied.

Mobile systems for monitoring Parkinson's disease

A challenge for the clinical management of Parkinson's disease (PD) is the large within- and between-patient variability in symptom profiles as well as the emergence of motor complications which represent a significant source of disability in patients. This thesis deals with the development and evaluation of methods and systems for supporting the management of PD by using repeated measures, consisting of subjective assessments of symptoms and objective assessments of motor function through fine motor tests (spirography and tapping), collected by means of a telemetry touch screen device. One aim of the thesis was to develop methods for objective quantification and analysis of the severity of motor impairments being represented in spiral drawings and tapping results. This was accomplished by first quantifying the digitized movement data with time series analysis and then using them in data-driven modelling for automating the process of assessment of symptom severity. The objective measures were then analysed with respect to subjective assessments of motor conditions. Another aim was to develop a method for providing comparable information content as clinical rating scales by combining subjective and objective measures into composite scores, using time series analysis and data-driven methods. The scores represent six symptom dimensions and an overall test score for reflecting the global health condition of the patient. In addition, the thesis presents the development of a web-based system for providing a visual representation of symptoms over time allowing clinicians to remotely monitor the symptom profiles of their patients. The quality of the methods was assessed by reporting different metrics of validity, reliability and sensitivity to treatment interventions and natural PD progression over time. Results from two studies demonstrated that the methods developed for the fine motor tests had good metrics indicating that they are appropriate to quantitatively and objectively assess the severity of motor impairments of PD patients. The fine motor tests captured different symptoms; spiral drawing impairment and tapping accuracy related to dyskinesias (involuntary movements) whereas tapping speed related to bradykinesia (slowness of movements). A longitudinal data analysis indicated that the six symptom dimensions and the overall test score contained important elements of information of the clinical scales and can be used to measure effects of PD treatment interventions and disease progression. A usability evaluation of the web-based system showed that the information presented in the system was comparable to qualitative clinical observations and the system was recognized as a tool that will assist in the management of patients.

Annual CO-emissions of combined pellet and solar heating systems

Emissions are an important aspect of a pellet heating system. High carbon monoxide emissions are often caused by unnecessary cycling of the burner when the burner is operated below the lowest combustion power. Combining pellet heating systems with a solar heating system can significantly reduce cycling of the pellet heater and avoid the inefficient summer operation of the pellet heater. The aim of this paper was to study CO-emissions of the different types of systems and to compare the yearly CO-emissions obtained from simulations with the yearly CO-emissions calculated based on the values that are obtained by the standard test methods. The results showed that the yearly CO-emissions obtained from the simulations are significant higher than the yearly CO-emissions calculated based on the standard test methods. It is also shown that for the studied systems the average emissions under these realistic annual conditions were greater than the limit values of two Eco-labels. Furthermore it could be seen that is possible to almost halve the CO-emission if the pellet heater is combined with a solar heating system.

Emissions Characterisation of residential pellet boilers during start-up and stop periods

In this study, gaseous emissions and particles are measured during start-up and stop periods for an over-fed boiler and an under-fed boiler. Both gaseous and particulate matter emissions are continuously measured in the laboratory. The measurement of gaseous emissions includes oxygen (O2), carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxide and (NO). The emissions rates are calculated from measured emissions concentrations and flue gas flow. The behaviours of the boilers during start-up and stop periods are analysed and the emissions are characterised in terms of CO, NO, TOC and particles (PM2.5 mass and number). The duration of the characterised periods vary between two boilers due to the difference in type of ignition and combustion control. The under-fed boiler B produces higher emissions during start-up periods than the over-fed boiler A. More hydrocarbon and particles are emitted by the under-fed boiler during stop periods. Accumulated mass of CO and TOC during start-up and stop periods contribute a major portion of the total mass emitted during whole operation. However, accumulated mass of NO and PM during start-up and stop periods are not significant as the duration of emission peak is relatively short.

EMISSIONS CHARACTERISTICS OF A RESIDENTIAL PELLET BOILER AND A STOVE

Gaseous and particulate emissions from a residential pellet boiler and a stove are measured at a realistic 6-day operation sequence and during steady state operation. The aim is to characterize the emissions during each phase in order to identify when the major part of the emissions occur to enable actions for emission reduction where the savings can be highest. The characterized emissions comprised carbon monoxide (CO), nitrogen oxide (NO), total organic carbon (TOC) and particulate matter (PM 2.5). In this study, emissions were characterised by mass concentration and emissions during start-up and stop phases were also presented in accumulated mass. The influence of start-up and stop phases on the emissions, average emission factors for the boiler and stove were analysed using the measured data from a six-days test. The share of start-up and stop emissions are significant for CO and TOC contributing 95% and 89% respectively at the 20kW boiler and 82% and 89% respectively at the 12 kW stove. NO and particles emissions are shown to dominate during stationary operation.

Decision Tree Classification Model In Water Supply Network

With the service life of water supply network (WSN) growth, the growing phenomenon of aging pipe network has become exceedingly serious. As urban water supply network is hidden underground asset, it is difficult for monitoring staff to make a direct classification towards the faults of pipe network by means of the modern detecting technology. In this paper, based on the basic property data (e.g. diameter, material, pressure, distance to pump, distance to tank, load, etc.) of water supply network, decision tree algorithm (C4.5) has been carried out to classify the specific situation of water supply pipeline. Part of the historical data was used to establish a decision tree classification model, and the remaining historical data was used to validate this established model. Adopting statistical methods were used to access the decision tree model including basic statistical method, Receiver Operating Characteristic (ROC) and Recall-Precision Curves (RPC). These methods has been successfully used to assess the accuracy of this established classification model of water pipe network. The purpose of classification model was to classify the specific condition of water pipe network. It is important to maintain the pipeline according to the classification results including asset unserviceable (AU), near perfect condition (NPC) and serious deterioration (SD). Finally, this research focused on pipe classification which plays a significant role in maintaining water supply networks in the future.

COMBUSTION and PYROLYSIS of A SLUDGE FROM WASTEWATER TREATMENT PLANT

The possibility of thermal treatment plants of municipal wastewater is an alternative solution for the final disposition of the sludge produced on small cities as Barueri, a small town of São Paulo State, Brazil. Combustion and pyrolysis of that municipal waste, occurring respectively in air and nitrogen, have been studied by thermogravimetry (TG) and differential thermal analysis (DTA). The main steps of each case were analyzed and Kissinger plots were used to estimate respective activation energies. DTG peaks are more indicated to represent the condition of maximum reaction rates than DTA peaks.

Análise preditiva a partir da caracterização das emissões gasosas e do óleo lubrificante em frotas com motorização a diesel

This work was motivated by the importance of conducting a study of vehicle emissions in captive fleets with diesel engine, coupled with the predictive maintenance plan. This type of maintenance includes techniques designed to meet the growing market demand to reduce maintenance costs by increasing the reliability of diagnoses, which has increased interest in automated predictive maintenance on diesel engines, preventing problems that might evolve into routine turn into serious situations, solved only with complex and costly repairs, the Reliability Centered Maintenance, will be the methodology that will make our goal is reached, beyond maintaining the vehicles regulated as fuel consumption and emissions. To Therefore, technical improvements were estimated capable of penetrating the automotive market and give the inshore fleet emission rates of opacity of the vehicles, being directly related to the conditions of the lubricating oil thus contributing to reducing maintenance costs by contributing significantly to emissions of pollutants and an improvement in the air in large cities. This criterion was adopted and implemented, em 241 buses and produced a diagnosis of possible failures by the correlation between the characterization of used lubricating oils and the analysis of opacity, with the objective of the aid the detection and solution of failures for the maintenance of sub-systems according to design criteria, and for this to be a deductive methodology to determine potential causes of failures, has been automated to implement a predictive maintenance system for this purpose was used in our study a mobile unit equipped with a opacimeter and a kit for collection and analysis of lubricating oil and the construction of the network diagnostics, we used a computer program in Microsoft Office Access 2007 platform tool is indispensable for creating a database data, this method is being used and successfully implemented in seven (7) bus companies from the city of Natal (RN) Brazil