Dynamic condition monitoring of buried gas pipes

This paper describes a device which can be used to detect variation in the integrity of the surrounding medium which supports buried gas pipes. The method is also applicable to other kinds of pipe. Variation in pipe support condition leads to increased likelihood of pipe damage under vehicle loading. A vibrating 'pig' has been developed and tested on buried pipelines in Britain and the measured data obtained is compared with theoretical models. Certain features, such as voids, hard spots and joints, display characteristic responses to vibration and a library of such characteristics has been constructed both experimentally and from the theoretical models.

Fibre optic distributed sensor system for condition monitoring of synthetic ropes

Reliability of the measuring devices is very important problem. Optical fibre sensors are very efficient. The use of optical fibre sensors for monitoring the physical and chemical parameters has been expanding over resent years. These sensors are applied for monitoring the structural integrity of long, parallel lay synthetic ropes. Such ropes are corrosion free, however, their operational lifetime under cyclic load is not well understood and premature failure can occur due to slippage and breakage of yarns within the rope. The monitoring system has been proposed which is based on acoustic detection of yarn breakage. Monitoring the strain and temperature is performed using the array of fibre gratings distributed along the rope length.

A condition monitoring platform using COTS wireless sensor networks - Lessons and experience

Developments in Micro-Electro-Mechanical Systems (MEMS), wireless communication systems and ad-hoc networking have created new dimensions to improve asset management not only during the operational phase but throughout an asset's lifecycle based on using improved quality of information obtained with respect to two key aspects of an asset: its location and condition. In this paper, we present our experience as well as lessons learnt from building a prototype condition monitoring platform to demonstrate and to evaluate the use of COTS wireless sensor networks to develop a prototype condition monitoring platform with the aim of improving asset management by providing accurate and real-time information. © 2010 IEEE.

Building Stone Condition Monitoring Using Specially Designed Compensated Optical Fiber Humidity Sensors

This paper presents the design and implementation of a novel optical fiber temperature compensated relative humidity (RH) sensor device, based on fiber Bragg gratings (FBGs) and developed specifically for monitoring water ingress leading to the deterioration of building stone. The performance of the sensor thus created, together with that of conventional sensors, was first assessed in the laboratory where they were characterized under experimental conditions of controlled wetting and drying cycles of limestone blocks, before being employed “in-the-field” to monitor actual building stone in a specially built wall. Although a new construction, this was built specifically using conservation methods similar to those employed in past centuries, to allow an accurate simulation of processes occurring with wetting and drying in the historic walls in the University of Oxford.

Fibre-optic strain sensor system with temperature compensation for arch bridge condition monitoring

This paper presents an innovative sensor system, created specifically for new civil engineering structural monitoring applications, allowing specially packaged fiber grating-based sensors to be used in harsh, in-the-field measurement conditions for accurate strain measurement with full temperature compensation. The sensor consists of two fiber Bragg gratings that are protected within a polypropylene package, with one of the fiber gratings isolated from the influence of strain and thus responding only to temperature variations, while the other is sensitive to both strain and temperature. To achieve this, the temperature-monitoring fiber grating is slightly bent and enclosed in a metal envelope to isolate it effectively from the strain. Through an appropriate calibration process, both the strain and temperature coefficients of each individual grating component when incorporated in the sensor system can be thus obtained. By using these calibrated coefficients in the operation of the sensor, both strain and temperature can be accurately determined. The specific application for which these sensors have been designed is seen when installed on an innovative small-scale flexi-arch bridge where they are used for real-time strain measurements during the critical installation stage (lifting) and loading. These sensors have demonstrated enhanced resilience when embedded in or surface-mounted on such concrete structures, providing accurate and consistent strain measurements not only during installation but subsequently during use. This offers an inexpensive and highly effective monitoring system tailored for the new, rapid method of the installation of small-scale bridges for a variety of civil engineering applications.

On-line diagnostics of transformer winding insulation failures, by Park`s vector approach

This paper presents a non-invasive approach for diagnosing winding insulation failures in three-phase transformers, which is based on the on-line monitoring of the primary and secondary current Park's Vector. Experimental and simulated results demonstrate the effectiveness of the proposed technique, for detecting winding inter-turn insulation faults in operating three-phase transformers.

Condition monitoring and diagnostics of power transformers

This paper addresses the subject of condition monitoring and diagnostics of power transformers. The main results of two reliability surveys, carried out under the auspices of CIGRE and IEEE in order to assemble objective data on the performance of transformers in service, are presented, providing useful information on the main causes of transformer failures, the most likely affected components and the related outages times. A survey of the most important methods, actually in use, for condition monitoring and diagnostics of power transformers is also given, which stresses the need for the development of new diagnostic methods, that can be applied without taking the transformers out of service, and that can also provide a fault severity criteria, in particular for determining transformers windings integrity. Preliminary results, concerning the on-going research activity on the development of a new approach for inter-turn winding fault diagnosis in three-phase transformers, are also reported in the paper.

Condition monitoring and diagnostics of power transformers

This paper addresses the subject of condition monitoring and diagnostics of power transformers. The main results of two reliability surveys, carried out under the auspices of CIGRE and IEEE in order to assemble objective data on the performance of transformers in service, are presented, providing useful information on the main causes of transformer failures, the most likely affected components and the related outages times. A survey of the most important methods, actually in use, for condition monitoring and diagnostics of power transformers is also given, which stresses the need for the development of new diagnostic methods, that can be applied without taking the transformers out of service, and that can also provide a fault severity criteria, in particular for determining transformers windings integrity. Preliminary results, concerning the on-going research activity on the development of a new approach for inter-turn winding fault diagnosis in three-phase transformers, are also reported in the paper.

A gestão pedagógica do ensino e aprendizagem on-line : especificidades

A gestão pedagógica do ensino e aprendizagem on-line: especificidades abordam os desafios da Gestão do Projeto Pedagógico que tem as Tecnologias de Informação e Comunicação por base didático-pedagógica. O fenômeno constitui-se na gestão do ensino-aprendizagem de curso lato senso a distância, no uso do computador conectado à internet, e a formação do educador especialista responsável pela coordenação, ensino, avaliação e/ou monitoria a frente do trabalho educativo. Reflete sobre os desafios da práxis pedagógica, subsidiada pela busca questionadora das tecnologias, a fim de responder também à demanda por inclusão sócio-digital. A abordagem metodológica de natureza qualitativa pauta-se na interpretação da realidade, de caráter hermenêutico com o intuito de considerar a experiência vivida pelos sujeitos na educação on-line a partir de uma visão crítica. Questiona o descompasso da educação formal brasileira e os avanços sociais com as incorporações de novas tecnologias de aprendizagens. Estabelece nas análises, a relação entre as teorias que sedimentam os objetivos do curso, as práticas de gestão e as influências ideológicas que marcam esse cenário, no PIGEAD da Universidade Federal Fluminense, Rio de Janeiro Brasil, período de 2010 a 2012. Os resultados desta pesquisa mostram que a interatividade, diferencial que aproxima o indivíduo e o torna parte da comunicação estabelecida na EAD on-line, não ocorre plenamente entre os sujeitos do processo. Além disso, a gestão democrática participativa declarada em seus objetivos de formação se mostra na realidade como prática centralizadora, sinalizando um descompasso entre teoria e prática. Esta pesquisa, entre outros, oferece elementos de avaliação e aprimoramento ao PIGEAD.

On-line prediction of cheese making using backscatter of near infrared indices light

The potential of a fibre optic sensor, detecting light backscatter in a cheese vat during coagulation and syneresis, to predict curd moisture, fat loses and curd yield was examined. Temperature, cutting time and calcium levels were varied to assess the strength of the predictions over a range of processing conditions. Equations were developed using a combination of independent variables, milk compositional and light backscatter parameters. Fat losses, curd yield and curd moisture content were predicted with a standard error of prediction (SEP) of +/- 2.65 g 100 g(-1) (R-2 = 0.93), +/- 0.95% (R-2 = 0.90) and +/- 1.43% (R-2 = 0.94), respectively. These results were used to develop a model for predicting curd moisture as a function of time during syneresis (SEP = +/- 1.72%; R-2 = 0.95). By monitoring coagulation and syneresis, this sensor technology could be employed to control curd moisture content, thereby improving process control during cheese manufacture. (c) 2007 Elsevier Ltd. All rights reserved..

Analysis of dietary pattern impact on weight status for personalised nutrition through on-line advice: the Food4Me Spanish cohort

Obesity prevalence is increasing. The management of this condition requires a detailed analysis of the global risk factors in order to develop personalised advice. This study is aimed to identify current dietary patterns and habits in Spanish population interested in personalised nutrition and investigate associations with weight status. Self-reported dietary and anthropometrical data from the Spanish participants in the Food4Me study, were used in a multidimensional exploratory analysis to define specific dietary profiles. Two opposing factors were obtained according to food groups’ intake: Factor 1 characterised by a more frequent consumption of traditionally considered unhealthy foods; and Factor 2, where the consumption of “Mediterranean diet” foods was prevalent. Factor 1 showed a direct relationship with BMI (β = 0.226; r2 = 0.259; p < 0.001), while the association with Factor 2 was inverse (β = −0.037; r2 = 0.230; p = 0.348). A total of four categories were defined (Prudent, Healthy, Western, and Compensatory) through classification of the sample in higher or lower adherence to each factor and combining the possibilities. Western and Compensatory dietary patterns, which were characterized by high-density foods consumption, showed positive associations with overweight prevalence. Further analysis showed that prevention of overweight must focus on limiting the intake of known deleterious foods rather than exclusively enhance healthy products.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Emission-based condition monitoring technique for ZnO surge arrester

In this paper, electromagnetic emission at the frequency range of 30MHz to 300MHz is used to detect physical defects on the 22kV outdoor zinc-oxide (ZnO) surge arresters. Different weather conditions combining with artificially created pollution were produced in a laboratory environment and measurements were recorded over a fixed period of time. Pollution due to fine dust particles has been created according to IEC standard under both wet and dry conditions. The aim is to detect the defects (bushing damage) when the surge arrester is subjected to various weather and surface condition. The collected electromagnetic signals were sampled and analyzed using analysis tools such as the autocorrelation coefficient and Wigner-Ville distribution. The results from the present paper indicate that electromagnetic radiation from the defects on surge arrester combining with the adequate analysis tools can be used as a valuable diagnostic tool for power system operator.