Effectiveness of Fluorescence-based Methods in Monitoring Progression of Noncavitated Caries-like Lesions on Smooth Surfaces

Although there has been a significant decrease in caries prevalence in developed countries, the slower progression of dental caries requires methods capable of detecting and quantifying lesions at an early stage. The aim of this study was to evaluate the effectiveness of fluorescence-based methods (DIAGNOdent 2095 laser fluorescence device [LF], DIAGNOdent 2190 pen [LFpen], and VistaProof fluorescence camera [FC]) in monitoring the progression of noncavitated caries-like lesions on smooth surfaces. Caries-like lesions were developed in 60 blocks of bovine enamel using a bacterial model of Streptococcus mutans and Lactobacillus acidophilus . Enamel blocks were evaluated by two independent examiners at baseline (phase I), after the first cariogenic challenge (eight days) (phase II), and after the second cariogenic challenge (a further eight days) (phase III) by two independent examiners using the LF, LFpen, and FC. Blocks were submitted to surface microhardness (SMH) and cross-sectional microhardness analyses. The intraclass correlation coefficient for intra- and interexaminer reproducibility ranged from 0.49 (FC) to 0.94 (LF/LFpen). SMH values decreased and fluorescence values increased significantly among the three phases. Higher values for sensitivity, specificity, and area under the receiver operating characteristic curve were observed for FC (phase II) and LFpen (phase III). A significant correlation was found between fluorescence values and SMH in all phases and integrated loss of surface hardness (ΔKHN) in phase III. In conclusion, fluorescence-based methods were effective in monitoring noncavitated caries-like lesions on smooth surfaces, with moderate correlation with SMH, allowing differentiation between sound and demineralized enamel.

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application.

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

Adaptive cross-device videoconferencing solution for wireless networks based on QoS monitoring

The increase in CPU power and screen quality of todays smartphones as well as the availability of high bandwidth wireless networks has enabled high quality mobile videoconfer- encing never seen before. However, adapting to the variety of devices and network conditions that come as a result is still not a trivial issue. In this paper, we present a multiple participant videoconferencing service that adapts to different kind of devices and access networks while providing an stable communication. By combining network quality detection and the use of a multipoint control unit for video mixing and transcoding, desktop, tablet and mobile clients can participate seamlessly. We also describe the cost in terms of bandwidth and CPU usage of this approach in a variety of scenarios.

RSA-Grid: A grid computing based framework for power system reliability and security analysis

Grid computing is an emerging technology for providing the high performance computing capability and collaboration mechanism for solving the collaborated and complex problems while using the existing resources. In this paper, a grid computing based framework is proposed for the probabilistic based power system reliability and security analysis. The suggested name of this computing grid is Reliability and Security Grid (RSA-Grid). Then the architecture of this grid is presented. A prototype system has been built for further development of grid-based services for power systems reliability and security assessment based on probabilistic techniques, which require high performance computing and large amount of memory. Preliminary results based on prototype of this grid show that RSA-Grid can provide the comprehensive assessment results for real power systems efficiently and economically.

Monitoring of centrifugal pump operation by a frequency converter

Centrifugal pumps are widely used in industrial and municipal applications, and they are an important end-use application of electric energy. However, in many cases centrifugal pumps operate with a significantly lower energy efficiency than they actually could, which typically has an increasing effect on the pump energy consumption and the resulting energy costs. Typical reasons for this are the incorrect dimensioning of the pumping system components and inefficiency of the applied pump control method. Besides the increase in energy costs, an inefficient operation may increase the risk of a pump failure and thereby the maintenance costs. In the worst case, a pump failure may lead to a process shutdown accruing additional costs. Nowadays, centrifugal pumps are often controlled by adjusting their rotational speed, which affects the resulting flow rate and output pressure of the pumped fluid. Typically, the speed control is realised with a frequency converter that allows the control of the rotational speed of an induction motor. Since a frequency converter can estimate the motor rotational speed and shaft torque without external measurement sensors on the motor shaft, it also allows the development and use of sensorless methods for the estimation of the pump operation. Still today, the monitoring of pump operation is based on additional measurements and visual check-ups, which may not be applicable to determine the energy efficiency of the pump operation. This doctoral thesis concentrates on the methods that allow the use of a frequency converter as a monitoring and analysis device for a centrifugal pump. Firstly, the determination of energy-efficiency- and reliability-based limits for the recommendable operating region of a variable-speed-driven centrifugal pump is discussed with a case study for the laboratory pumping system. Then, three model-based estimation methods for the pump operating location are studied, and their accuracy is determined by laboratory tests. In addition, a novel method to detect the occurrence of cavitation or flow recirculation in a centrifugal pump by a frequency converter is introduced. Its sensitivity compared with known cavitation detection methods is evaluated, and its applicability is verified by laboratory measurements for three different pumps and by using two different frequency converters. The main focus of this thesis is on the radial flow end-suction centrifugal pumps, but the studied methods can also be feasible with mixed and axial flow centrifugal pumps, if allowed by their characteristics.

A New Model For Reliability Centered Maintenance In Petroleum Refineries

Refiners today operate their equipment for prolonged periods without shutdown. This is primarily due to the increased pressures of the market resulting in extended shutdown-to-shutdown intervals. This places extreme demands on the reliability of the plant equipment. The traditional methods of reliability assurance, like Preventive Maintenance, Predictive Maintenance and Condition Based Maintenance become inadequate in the face of such demands. The alternate approaches to reliability improvement, being adopted the world over are implementation of RCFA programs and Reliability Centered Maintenance. However refiners and process plants find it difficult to adopt this standardized methodology of RCM mainly due to the complexity and the large amount of analysis that needs to be done, resulting in a long drawn out implementation, requiring the services of a number of skilled people. These results in either an implementation restricted to only few equipment or alternately, one that is non-standard. The paper presents the current models in use, the core requirements of a standard RCM model, the alternatives to classical RCM, limitations in the existing model, classical RCM and available alternatives to RCM and will then go on to present an ‗Accelerated‘ approach to RCM implementation, that, while ensuring close conformance to the standard, does not place a large burden on the implementers

Estratégias de implementação de plataformas de e-maintenance na indústria: desenvolvimento de uma aplicação para um sistema logístico de viaturas

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

The importance of control monitoring systems in wind parks maintenance

The objective of every wind energy producer is to reduce operational costs associated to the production as a way to increase profits. One other issue that must be looked carefully is the equipment maintenance. Increase the availability of wind turbines by reducing the downtime associated to failures is a good strategy to achieve the main goal of increase profits. As a way to help in the definition of the best maintenance strategies, condition monitoring systems (CMS) have an important role to play. Informatics tools to make the condition monitoring of the wind turbines were developed and are now being installed as a way to help producers reducing the operational costs. There are a lot of developed systems to do the monitoring of a wind turbine or the whole wind park, in this paper will be made an overview of the most important systems.

An Adaptive Field Detection Method For Bridge Scour Monitoring Using Motion-Sensing Radio Transponders (RFIDs), TR-617, 2014

A comprehensive field detection method is proposed that is aimed at developing advanced capability for reliable monitoring, inspection and life estimation of bridge infrastructure. The goal is to utilize Motion-Sensing Radio Transponders (RFIDS) on fully adaptive bridge monitoring to minimize the problems inherent in human inspections of bridges. We developed a novel integrated condition-based maintenance (CBM) framework integrating transformative research in RFID sensors and sensing architecture, for in-situ scour monitoring, state-of-the-art computationally efficient multiscale modeling for scour assessment.

Kunnossapidon kehitysmalli sanomalehtipainon tuotannon luotettavuuden, tuottavuuden ja tuotteen laadun turvaamiseksi

Diplomityössä käsitellään ne toimet, jotka Esa Lehtipaino Oy:ssä tarvitsee tehdä kunnossapidon kehittämiseksi sanomalehtipainoprosessin kunnossapidossa. Työssä käytettiin luotettavuuskeskeisen ja kokonaisvaltaisen tuottavuuskeskeisen kunnossapidon strategioiden osia sekä PSK Standardisoinnin PSK 5705:2006standardin mukaista menetelmää määrittämään kunnossapidon kannalta tärkeimmät kohteet ja osa-alueet. PSK 5705:2006 on kunnonvalvonnan värähtelymittausten mittaustoiminnan suunnitteluun luotu standardi, jonka perusteella rakennettiin sanomalehtipainoprosessiin sopiva tuotantolaitteiston luokitusjärjestelmä. Luokituksenperusteella kohdennetaan kunnossapidon resurssit tuotantojärjestelmän luotettavuuden kannalta oikeisiin, tuottavimpiin kohteisiin. Tuotantohenkilöstön kunnossapitohenkilökunnalle tekemien vikailmoitusten välitykseen rakennettiin Microsoft Access -pohjainen Vikaloki-lomake. Kunnossapitotoiminnan kehityksen tuloksien seuraamiseksi määritettiin PSK 6201:2003 standardin mukainen tuotannon kokonaistehokkuutta kuvaava KNL-luku. KNL-luvusta luotiin ennuste kunnossapidon kehittämistarpeista regressioanalyysin avulla. Kehitysmalli esittää, että kohdeyrityksessä tulee toiminnan kehittäminen aloittaa päivittämällä tietokonepohjainen toiminnanohjausjärjestelmä, johon lisätään ennakoivat suunnitellut kunnossapitotoimet. Toimet määriteltiin yllämainitun kriittisyysluokituksen perusteella.

PGW-linjan käyttövarmuuden ja kunnossapidon tehokuuden parantaminen kiinteällä kunnonvalvonnalla

Tämän diplomityön lähtökohtana on tutkia kiinteän kunnonvalvonnan ja ehkäisevän kunnossapidon edellytyksiä ja mahdollisuuksia Anjalan Paperitehtaan painehiomossa. Työn tavoitteena on kunnossapidon kustannustehokkuuden parantaminen ja häiriöaikojen vähentäminen ja sitä kautta koko tuotantoprosessin tuottavuuden nostaminen. Työn alussa tarkastellaan tämänhetkisiä prosessilaitteiston häiriötekijöitä ja kunnossapidon vaikutusmahdollisuuksia häiriöiden korjaukseen ja kustannuksiin. Tarkastelun perusteella päädyttiin painehiomossa ehkäisevän kunnossapidon määrän nostamiseen ja kiinteän kunnonvalvontajärjestelmän käyttöönottoon H4-linjalla. Jatkuvatoimisen kunnonvalvonnan edut tutkimuksen ja teorian perusteella ovat laitteiden käyttövarmuuden olennainen paraneminen ja kunnossapitokustannusten aleneminen. Työn kokeellisen osan perusteella kunnossapitokustannukset alenivat noin 24 % ja käytettävyyden tehostumisen johdosta laitehäiriöt alenivat 50 %:lla. Tulokset saatiin aikaan toteuttamalla suunnitellut ehkäisevät huollot kriittisille laitteille. Kiinteä kunnonvalvonta antoi kunnossapidolle tiedon laitteiden oikea-aikaisesta huoltovälistä. Investoinnin hyödyt saatiin täysmääräisesti käyttöön jo laitteiston ensimmäisen käyttövuoden aikana. Henkilöstön osaamiskapasiteetin nosto tulee vielä lisäämään edellä mainittuja hyötyjä.

Kompressoriyksiköiden mekaaninen kunnonhallinta

Kunnossapidon kuluista suurimman osan aiheuttavat koneiden ennakoimattomat rikkoutumiset ja niiden tuomat tuotannonpysäytykset. Kunnossapidon suunnitelmallisuutta ja vikojen ennustettavuutta pyritään parantamaan erilaisin kunnonvalvonnallisin keinoin. Havaitsemalla alkava vikaantuminen ajoissa ja seuraamalla sen kehittymistä luodaan mahdollisuus korjaustoimenpiteiden ja -ajankohdan hallittuun suunnitteluun ja tätä kautta kustannussäästöihin. Tässä työssä on tutkittu kompressoriyksiköiden (kaasuturbiini ja keskipakokompressori) ja niiden apulaitteiden kunnossapidon menetelmiä, niiden hyödynnettävyyttä sekä mahdollisuuksia kehittää mekaanista kunnonhallintaa. Työssä päädyttiin johtopäätökseen, että käytettävien menetelmien hyödynnettävyydessä on kehitettävää. Kunnonvalvonnan ohjeistuksia tarkennettiin vastaamaan tämän päivän tavoitteita. Todettiin myös, että värähtelynvalvontaan perustuva kunnonvalvontajärjestelmä soveltuu hyvin kompressoriyksiköiden kunnonvalvonnan järjestelmäksi. Värähtelynvalvontaan perustuva kunnonvalvontajärjestelmä luo mahdollisuuden turvallisen käyttöajan ennustamiseen. Kunnonvalvonnan kehittämisen ja käyttövarmuuden parantamisen kannalta jatkotutkimuksen tekeminen kompressoriyksiköiden mekaanistenlaitteiden turvallisen käyttöajan ennustamiseksi on perusteltua.

MACHINE VISION FOR AUTOMATICVISUAL INSPECTION OF WOODENRAILWAY SLEEPERS USING UNSUPERVISED NEURAL NETWORKS

The motivation for this thesis work is the need for improving reliability of equipment and quality of service to railway passengers as well as a requirement for cost-effective and efficient condition maintenance management for rail transportation. This thesis work develops a fusion of various machine vision analysis methods to achieve high performance in automation of wooden rail track inspection.The condition monitoring in rail transport is done manually by a human operator where people rely on inference systems and assumptions to develop conclusions. The use of conditional monitoring allows maintenance to be scheduled, or other actions to be taken to avoid the consequences of failure, before the failure occurs. Manual or automated condition monitoring of materials in fields of public transportation like railway, aerial navigation, traffic safety, etc, where safety is of prior importance needs non-destructive testing (NDT).In general, wooden railway sleeper inspection is done manually by a human operator, by moving along the rail sleeper and gathering information by visual and sound analysis for examining the presence of cracks. Human inspectors working on lines visually inspect wooden rails to judge the quality of rail sleeper. In this project work the machine vision system is developed based on the manual visual analysis system, which uses digital cameras and image processing software to perform similar manual inspections. As the manual inspection requires much effort and is expected to be error prone sometimes and also appears difficult to discriminate even for a human operator by the frequent changes in inspected material. The machine vision system developed classifies the condition of material by examining individual pixels of images, processing them and attempting to develop conclusions with the assistance of knowledge bases and features.A pattern recognition approach is developed based on the methodological knowledge from manual procedure. The pattern recognition approach for this thesis work was developed and achieved by a non destructive testing method to identify the flaws in manually done condition monitoring of sleepers.In this method, a test vehicle is designed to capture sleeper images similar to visual inspection by human operator and the raw data for pattern recognition approach is provided from the captured images of the wooden sleepers. The data from the NDT method were further processed and appropriate features were extracted.The collection of data by the NDT method is to achieve high accuracy in reliable classification results. A key idea is to use the non supervised classifier based on the features extracted from the method to discriminate the condition of wooden sleepers in to either good or bad. Self organising map is used as classifier for the wooden sleeper classification.In order to achieve greater integration, the data collected by the machine vision system was made to interface with one another by a strategy called fusion. Data fusion was looked in at two different levels namely sensor-level fusion, feature- level fusion. As the goal was to reduce the accuracy of the human error on the rail sleeper classification as good or bad the results obtained by the feature-level fusion compared to that of the results of actual classification were satisfactory.