933 resultados para condition monitoring system


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The objective of industrial crystallization is to obtain a crystalline product which has the desired crystal size distribution, mean crystal size, crystal shape, purity, polymorphic and pseudopolymorphic form. Effective control of the product quality requires an understanding of the thermodynamics of the crystallizing system and the effects of operation parameters on the crystalline product properties. Therefore, obtaining reliable in-line information about crystal properties and supersaturation, which is the driving force of crystallization, would be very advantageous. Advanced techniques, such asRaman spectroscopy, attenuated total reflection Fourier transform infrared (ATR FTIR) spectroscopy, and in-line imaging techniques, offer great potential for obtaining reliable information during crystallization, and thus giving a better understanding of the fundamental mechanisms (nucleation and crystal growth) involved. In the present work, the relative stability of anhydrate and dihydrate carbamazepine in mixed solvents containing water and ethanol were investigated. The kinetics of the solvent mediated phase transformation of the anhydrate to hydrate in the mixed solvents was studied using an in-line Raman immersion probe. The effects of the operation parameters in terms of solvent composition, temperature and the use of certain additives on the phase transformation kineticswere explored. Comparison of the off-line measured solute concentration and the solid-phase composition measured by in-line Raman spectroscopy allowedthe identification of the fundamental processes during the phase transformation. The effects of thermodynamic and kinetic factors on the anhydrate/hydrate phase of carbamazepine crystals during cooling crystallization were also investigated. The effect of certain additives on the batch cooling crystallization of potassium dihydrogen phosphate (KDP) wasinvestigated. The crystal growth rate of a certain crystal face was determined from images taken with an in-line video microscope. An in-line image processing method was developed to characterize the size and shape of thecrystals. An ATR FTIR and a laser reflection particle size analyzer were used to study the effects of cooling modes and seeding parameters onthe final crystal size distribution of an organic compound C15. Based on the obtained results, an operation condition was proposed which gives improved product property in terms of increased mean crystal size and narrowersize distribution.

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In this thesis a control system for an intelligent low voltage energy grid is presented, focusing on the control system created by using a multi-agent approach which makes it versatile and easy to expand according to the future needs. The control system is capable of forecasting the future energy consumption and decisions making on its own without human interaction when countering problems. The control system is a part of the St. Petersburg State Polytechnic University’s smart grid project that aims to create a smart grid for the university’s own use. The concept of the smart grid is interesting also for the consumers as it brings new possibilities to control own energy consumption and to save money. Smart grids makes it possible to monitor the energy consumption in real-time and to change own habits to save money. The intelligent grid also brings possibilities to integrate the renewable energy sources to the global or the local energy production much better than the current systems. Consumers can also sell their extra power to the global grid if they want.

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This paper investigates defect detection methodologies for rolling element bearings through vibration analysis. Specifically, the utility of a new signal processing scheme combining the High Frequency Resonance Technique (HFRT) and Adaptive Line Enhancer (ALE) is investigated. The accelerometer is used to acquire data for this analysis, and experimental results have been obtained for outer race defects. Results show the potential effectiveness of the signal processing technique to determine both the severity and location of a defect. The HFRT utilizes the fact that much of the energy resulting from a defect impact manifests itself in the higher resonant frequencies of a system. Demodulation of these frequency bands through use of the envelope technique is then employed to gain further insight into the nature of the defect while further increasing the signal to noise ratio. If periodic, the defect frequency is then present in the spectra of the enveloped signal. The ALE is used to enhance the envelope spectrum by reducing the broadband noise. It provides an enhanced envelope spectrum with clear peaks at the harmonics of a characteristic defect frequency. It is implemented by using a delayed version of the signal and the signal itself to decorrelate the wideband noise. This noise is then rejected by the adaptive filter that is based upon the periodic information in the signal. Results have been obtained for outer race defects. They show the effectiveness of the methodology to determine both the severity and location of a defect. In two instances, a linear relationship between signal characteristics and defect size is indicated.

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Modern computer systems are plagued with stability and security problems: applications lose data, web servers are hacked, and systems crash under heavy load. Many of these problems or anomalies arise from rare program behavior caused by attacks or errors. A substantial percentage of the web-based attacks are due to buffer overflows. Many methods have been devised to detect and prevent anomalous situations that arise from buffer overflows. The current state-of-art of anomaly detection systems is relatively primitive and mainly depend on static code checking to take care of buffer overflow attacks. For protection, Stack Guards and I-leap Guards are also used in wide varieties.This dissertation proposes an anomaly detection system, based on frequencies of system calls in the system call trace. System call traces represented as frequency sequences are profiled using sequence sets. A sequence set is identified by the starting sequence and frequencies of specific system calls. The deviations of the current input sequence from the corresponding normal profile in the frequency pattern of system calls is computed and expressed as an anomaly score. A simple Bayesian model is used for an accurate detection.Experimental results are reported which show that frequency of system calls represented using sequence sets, captures the normal behavior of programs under normal conditions of usage. This captured behavior allows the system to detect anomalies with a low rate of false positives. Data are presented which show that Bayesian Network on frequency variations responds effectively to induced buffer overflows. It can also help administrators to detect deviations in program flow introduced due to errors.

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Geochemical composition is a set of data for predicting the climatic condition existing in an ecosystem. Both the surficial and core sediment geochemistry are helpful in monitoring, assessing and evaluating the marine environment. The aim of the research work is to assess the relationship between the biogeochemical constituents in the Cochin Estuarine System (CES), their modifications after a long period of anoxia and also to identify the various processes which control the sediment composition in this region, through a multivariate statistical approach. Therefore the study of present core sediment geochemistry has a critical role in unraveling the benchmark of their characterization. Sediment cores from four prominent zones of CES were examined for various biogeochemical aspects. The results have served as rejuvenating records for the prediction of core sediment status prevailing in the CES

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Geochemical composition is a set of data for predicting the climatic condition existing in an ecosystem. Both the surficial and core sediment geochemistry are helpful in monitoring, assessing and evaluating the marine environment. The aim of the research work is to assess the relationship between the biogeochemical constituents in the Cochin Estuarine System (CES), their modifications after a long period of anoxia and also to identify the various processes which control the sediment composition in this region, through a multivariate statistical approach. Therefore the study of present core sediment geochemistry has a critical role in unraveling the benchmark of their characterization. Sediment cores from four prominent zones of CES were examined for various biogeochemical aspects. The results have served as rejuvenating records for the prediction of core sediment status prevailing in the CES

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The long-term stability, high accuracy, all-weather capability, high vertical resolution, and global coverage of Global Navigation Satellite System (GNSS) radio occultation (RO) suggests it as a promising tool for global monitoring of atmospheric temperature change. With the aim to investigate and quantify how well a GNSS RO observing system is able to detect climate trends, we are currently performing an (climate) observing system simulation experiment over the 25-year period 2001 to 2025, which involves quasi-realistic modeling of the neutral atmosphere and the ionosphere. We carried out two climate simulations with the general circulation model MAECHAM5 (Middle Atmosphere European Centre/Hamburg Model Version 5) of the MPI-M Hamburg, covering the period 2001–2025: One control run with natural variability only and one run also including anthropogenic forcings due to greenhouse gases, sulfate aerosols, and tropospheric ozone. On the basis of this, we perform quasi-realistic simulations of RO observables for a small GNSS receiver constellation (six satellites), state-of-the-art data processing for atmospheric profiles retrieval, and a statistical analysis of temperature trends in both the “observed” climatology and the “true” climatology. Here we describe the setup of the experiment and results from a test bed study conducted to obtain a basic set of realistic estimates of observational errors (instrument- and retrieval processing-related errors) and sampling errors (due to spatial-temporal undersampling). The test bed results, obtained for a typical summer season and compared to the climatic 2001–2025 trends from the MAECHAM5 simulation including anthropogenic forcing, were found encouraging for performing the full 25-year experiment. They indicated that observational and sampling errors (both contributing about 0.2 K) are consistent with recent estimates of these errors from real RO data and that they should be sufficiently small for monitoring expected temperature trends in the global atmosphere over the next 10 to 20 years in most regions of the upper troposphere and lower stratosphere (UTLS). Inspection of the MAECHAM5 trends in different RO-accessible atmospheric parameters (microwave refractivity and pressure/geopotential height in addition to temperature) indicates complementary climate change sensitivity in different regions of the UTLS so that optimized climate monitoring shall combine information from all climatic key variables retrievable from GNSS RO data.

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This paper describes an assessment of the nitrogen and phosphorus dynamics of the River Kennet in the south east of England. The Kennet catchment (1200 km(2)) is a predominantly groundwater fed river impacted by agricultural and sewage sources of nutrient (nitrogen and phosphorus) pollution. The results from a suite of simulation models are integrated to assess the key spatial and temporal variations in the nitrogen (N) and phosphorus (P) chemistry, and the influence of changes in phosphorous inputs from a Sewage Treatment Works on the macrophyte and epiphyte growth patterns. The models used are the Export Co-efficient model, the Integrated Nitrogen in Catchments model, and a new model of in-stream phosphorus and macrophyte dynamics: the 'Kennet' model. The paper concludes with a discussion on the present state of knowledge regarding the water quality functioning, future research needs regarding environmental modelling and the use of models as management tools for large, nutrient impacted riverine systems. (C) 2003 IMACS. Published by Elsevier B.V. All rights reserved.

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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, a faulty, system or application software. Desirable characteristics for monitoring systems are the ability to connect to any number of different types of monitoring agents and to provide different views of the system, based on a client's particular preferences. This paper outlines and discusses the ongoing activities within the GridRM wide-area resource-monitoring project.

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Weekly monitoring of profiles of student performances on formative and summative coursework throughout the year can be used to quickly identify those who need additional help, possibly due to acute and sudden-onset problems. Such an early-warning system can help retention, but also assist students in overcoming problems early on, thus helping them fulfil their potential in the long run. We have developed a simple approach for the automatic monitoring of student mark profiles for individual modules, which we intend to trial in the near future. Its ease of implementation means that it can be used for very large cohorts with little additional effort when marks are already collected and recorded on a spreadsheet.

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Limnologists had an early preoccupation with lake classification. It gave a necessary structure to the many chemical and biological observations that were beginning to form the basis of one of the earliest truly environmental sciences. August Thienemann was the doyen of such classifiers and his concept with Einar Naumann of oligotrophic and eutrophic lakes remains central to the world-view that limnologists still have. Classification fell into disrepute, however, as it became clear that there would always be lakes that deviated from the prescriptions that the classifiers made for them. Continua became the de rigeur concept and lakes were seen as varying along many chemical, biological and geographic axes. Modern limnologists are comfortable with this concept. That all lakes are different guarantees an indefinite future for limnological research. For those who manage lakes and the landscapes in which they are set, however, it is not very useful. There may be as many as 300000 standing water bodies in England and Wales alone and maybe as many again in Scotland. More than 80 000 are sizable (> 1 ha). Some classification scheme to cope with these numbers is needed and, as human impacts on them increase, a system of assessing and monitoring change must be built into such a scheme. Although ways of classifying and monitoring running waters are well developed in the UK, the same is not true of standing waters. Sufficient understanding of what determines the nature and functioning of lakes exists to create a system which has intellectual credibility as well as practical usefulness. This paper outlines the thinking behind a system which will be workable on a north European basis and presents some early results.