Kunnossapidon työlupakäytäntöjen parantaminen mobiilijärjestelmän avulla

Viranomaisvaatimuksen mukaan ydinvoimalaitoksen toiminnan perustana tulee olla johtamisjärjestelmä, joka kattaa organisaation rakenteen ja prosessit, henkilöstön vastuut ja valtuudet sekä päätöksentekomenettelyt. Sen tulee myös tukea hyvää turvallisuuskulttuuria ja varmistaa että ydin- ja säteilyturvallisuuteen liittyvät vaatimukset täyttyvät kaikessa toiminnassa. Loviisan voimalaitoksen johtamisjärjestelmä ohjaa voimalaitoksen käyttötoimintaa ja se on kuvattuna voimalaitosohjeistossa joka käsittää voimalaitoksen politiikat, laadunvarmistuskäsikirjat sekä erilaiset ohjeet. Loviisan voimalaitoksen toimintaa seurataan ja arvioidaan säännöllisesti mm. auditoinneilla. Seurannan ja arvioinnin tarkoituksena on tunnistaa johtamisjärjestelmän mahdolliset kehittämisalueet ja varmistaa täyttääkö toiminta sille asetetut vaatimukset. Tämä opinnäyte pohjautuu sisäisessä auditoinnissa havaittuun puutteeseen voimalaitoksen työlupakäytännöissä. Työssä toteutettiin mobiilijärjestelmä, jonka tarkoituksena on parantaa kunnossapitotöihin liittyvien työlupien jälkiseurantaa. Tällaisia työlupaa vaativia töitä ovat mm. tuli- ja säteilytyöt, joiden suorittamiseen liittyy riskejä kuten palo- ja räjähdysvaara tai tarpeeton altistuminen säteilylle. Mobiilijärjestelmä toteutettiin monikansallisena projektina osana laajempaa Loviisan voimalaitoksen laitostietojärjestelmän uusintaprojektia.

Sähkökemiallisten mittausmenetelmien hyödyntäminen optimaalisessa kunnossapidossa

Sähkökemiallisia korroosionopeuden mittausmenetelmiä, yhdistettynä rakennema-teriaalien ohenemaseurantaan, on edelleen harvoin hyödynnetty toimilaitteiden ja rakenteiden elinkaarihallintaan liittyvässä kunnossapidossa. Tässä diplomityössä selvitetään sähkökemiallisten korroosiomittausten käyttöä optimaalisen kunnossapidon apuvälineenä. Työssä selvitetään erityisesti sähkö-kemiallisten mittausjärjestelmien soveltuvuutta voimalaitosten tulistinalueen kor-roosion sekä kylmäpään happo- ja vesikastepisteen mittaamiseen ja kriittisen kas-tepistelämpötilan määrittämiseen. Lisäksi selvitetään mittausten soveltuvuut-ta voimalaitosten polttoainehallinnan optimointiin sekä teknis-taloudellisuuteen perustuvaan prosessin säätämiseen. / Electrochemical corrosion rate measuring methods have been used years in indus-trial maintenance research. Still electrochemical corrosion rate measurement methods are rarely used in the industrial maintenance work related to the life cycle of equipment and structures. This work will study the suitability and use of electrochemical corrosion meas-urements in the optimum maintenance. The work will specifically address the suitability of electrochemical measuring systems for power plants super heater and the cold end corrosion monitoring. Study focus on acid and water dew point monitoring and the determination of the critical dew point temperature. In addi-tion, study the suitability of measurements of power plant fuel management as well as techno-economics based on the process of adjustment.

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.

A synthetic control chart for monitoring the process mean and variance

Purpose - The aim of this paper is to present a synthetic chart based on the non-central chi-square statistic that is operationally simpler and more effective than the joint X̄ and R chart in detecting assignable cause(s). This chart will assist in identifying which (mean or variance) changed due to the occurrence of the assignable causes. Design/methodology/approach - The approach used is based on the non-central chi-square statistic and the steady-state average run length (ARL) of the developed chart is evaluated using a Markov chain model. Findings - The proposed chart always detects process disturbances faster than the joint X̄ and R charts. The developed chart can monitor the process instead of looking at two charts separately. Originality/value - The most important advantage of using the proposed chart is that practitioners can monitor the process by looking at only one chart instead of looking at two charts separately. © Emerald Group Publishing Limted.

Design of a labVIEW system applied to predictive maintenance

The implementation of vibration analysis techniques based on virtual instrumentation has spread increasingly in the academic and industrial branch, since the use of any software for this type of analysis brings good results at low cost. Among the existing software for programming and creation of virtual instruments, the LabVIEW was chosen for this project. This software has good interface with the method of graphical programming. In this project, it was developed a system of rotating machine condition monitoring. This monitoring system is applied in a test stand, simulating large scale applications, such as in hydroelectric, nuclear and oil exploration companies. It was initially used a test stand, where an instrumentation for data acquisition was inserted, composed of accelerometers and inductive proximity sensors. The data collection system was structured on the basis of an NI 6008 A/D converter of National Instruments. An electronic circuit command was developed through the A/D converter for a remote firing of the test stand. The equipment monitoring is performed through the data collected from the sensors. The vibration signals collected by accelerometers are processed in the time domain and frequency. Also, proximity probes were used for the axis orbit evaluation and an inductive sensor for the rotation and trigger measurement. © (2013) Trans Tech Publications, Switzerland.

Aplicação de um sistema de monitoramento remoto para auxiliar na manutenção preditiva e preventiva de componentes de uma subestação

The increase in energy consumption in the world has caused the electrical systems becoming ever larger and more complex. Because of that becomes necessary to use special tools to efficiently manage the equipment present in these systems. Nowadays a tool very used is the remote monitoring of assets which works collecting signals using sensors processing these signals and make them available to the system user. So the user can use informations that may assist him efficiently in making decisions when doing a maintenance. The system is technically efficient since it improves the measurement process and enables the asset management of a substation by using advanced technology for that and economically viable especially in cases where the user is subject to monetary loss due an interruption of power supply

Space charge and dielectric response measurements to assess insulation aging of low-voltage cables used in nuclear power plants

The current design life of nuclear power plant (NPP) could potentially be extended to 80 years. During this extended plant life, all safety and operationally relevant Instrumentation & Control (I&C) systems are required to meet their designed performance requirements to ensure safe and reliable operation of the NPP, both during normal operation and subsequent to design base events. This in turn requires an adequate and documented qualification and aging management program. It is known that electrical insulation of I&C cables used in safety related circuits can degrade during their life, due to the aging effect of environmental stresses, such as temperature, radiation, vibration, etc., particularly if located in the containment area of the NPP. Thus several condition monitoring techniques are required to assess the state of the insulation. Such techniques can be used to establish a residual lifetime, based on the relationship between condition indicators and ageing stresses, hence, to support a preventive and effective maintenance program. The object of this thesis is to investigate potential electrical aging indicators (diagnostic markers) testing various I&C cable insulations subjected to an accelerated multi-stress (thermal and radiation) aging.

Selecting a preventive maintenance treatment for flexible pavements /

"August 2000."

Maintenance strategies affecting equipment performance

Proper maintenance of plant items is crucial for the safe and profitable operation of process plants, The relevant maintenance policies fall into the following four categories: (i) preventivejopportunistic/breakdown replacement policies, (ii) inspection/inspection-repair-replacernent policies, (iii) restorative maintenance policies, and (iv) condition based maintenance policies, For correlating failure times of component equipnent and complete systems, the Weibull failure distribution has been used, A new powerful method, SEQLIM, has been proposed for the estimation of the Weibull parameters; particularly, when maintenance records contain very few failures and many successful operation times. When a system consists of a number of replaceable, ageing components, an opporturistic replacernent policy has been found to be cost-effective, A simple opportunistic rrodel has been developed. Inspection models with various objective functions have been investigated, It was found that, on the assumption of a negative exponential failure distribution, all models converge to the same optimal inspection interval; provided the safety components are very reliable and the demand rate is low, When deterioration becomes a contributory factor to same failures, periodic inspections, calculated from above models, are too frequent, A case of safety trip systems has been studied, A highly effective restorative maintenance policy can be developed if the performance of the equipment under this category can be related to some predictive modelling. A novel fouling model has been proposed to determine cleaning strategies of condensers, Condition-based maintenance policies have been investigated. A simple gauge has been designed for condition monitoring of relief valve springs. A typical case of an exothermic inert gas generation plant has been studied, to demonstrate how various policies can be applied to devise overall maintenance actions.

In situ diagnostics and prognostics of solder fatigue in IGBT modules for electric vehicle drives

This paper proposes an in situ diagnostic and prognostic (D&P) technology to monitor the health condition of insulated gate bipolar transistors (IGBTs) used in EVs with a focus on the IGBTs' solder layer fatigue. IGBTs' thermal impedance and the junction temperature can be used as health indicators for through-life condition monitoring (CM) where the terminal characteristics are measured and the devices' internal temperature-sensitive parameters are employed as temperature sensors to estimate the junction temperature. An auxiliary power supply unit, which can be converted from the battery's 12-V dc supply, provides power to the in situ test circuits and CM data can be stored in the on-board data-logger for further offline analysis. The proposed method is experimentally validated on the developed test circuitry and also compared with finite-element thermoelectrical simulation. The test results from thermal cycling are also compared with acoustic microscope and thermal images. The developed circuitry is proved to be effective to detect solder fatigue while each IGBT in the converter can be examined sequentially during red-light stopping or services. The D&P circuitry can utilize existing on-board hardware and be embedded in the IGBT's gate drive unit.

In situ diagnostics and prognostics of wire bonding faults in IGBT modules for electric vehicle drives

This paper presents a diagnostic and prognostic condition monitoring method for insulated-gate bipolar transistor (IGBT) power modules for use primarily in electric vehicle applications. The wire-bond-related failure, one of the most commonly observed packaging failures, is investigated by analytical and experimental methods using the on-state voltage drop as a failure indicator. A sophisticated test bench is developed to generate and apply the required current/power pulses to the device under test. The proposed method is capable of detecting small changes in the failure indicators of the IGBTs and freewheeling diodes and its effectiveness is validated experimentally. The novelty of the work lies in the accurate online testing capacity for diagnostics and prognostics of the power module with a focus on the wire bonding faults, by injecting external currents into the power unit during the idle time. Test results show that the IGBT may sustain a loss of half the bond wires before the impending fault becomes catastrophic. The measurement circuitry can be embedded in the IGBT drive circuits and the measurements can be performed in situ when the electric vehicle stops in stop-and-go, red light traffic conditions, or during routine servicing.

Ferramentas para análise de ativos em redes industriais weirelessHART

Nowadays wireless communication has emerged as a tendency in industry environments. In part this interest is due to the ease of deployment and maintenance, which dispenses sophisticated designs and wired infrastructure (which in industrial environment often prohibitively expensive) besides enabling the addition of new applications when compared to their wired counterparts. Despite its high degree of applicability, an industrial wireless sensor network faces some challenges. One of the most challenging problems are its reliability, energy consumption and the environment interference. In this dissertation will discuss the problem of asset analysis in wireless industrial networks for the WirelessHART standard by implementing a monitoring system. The system allows to carry out various activities of independent asset management manufacturers, such as prediction of battery life, maintenance, reliability data, topology, and the possibility of creating new metrics from open and standardized development libraries. Through the implementation of this tool is intended to contribute to integration of wireless technologies in industrial environments.

Availability estimation and management for complex processing systems

“Availability” is the terminology used in asset intensive industries such as petrochemical and hydrocarbons processing to describe the readiness of equipment, systems or plants to perform their designed functions. It is a measure to suggest a facility’s capability of meeting targeted production in a safe working environment. Availability is also vital as it encompasses reliability and maintainability, allowing engineers to manage and operate facilities by focusing on one performance indicator. These benefits make availability a very demanding and highly desired area of interest and research for both industry and academia. In this dissertation, new models, approaches and algorithms have been explored to estimate and manage the availability of complex hydrocarbon processing systems. The risk of equipment failure and its effect on availability is vital in the hydrocarbon industry, and is also explored in this research. The importance of availability encouraged companies to invest in this domain by putting efforts and resources to develop novel techniques for system availability enhancement. Most of the work in this area is focused on individual equipment compared to facility or system level availability assessment and management. This research is focused on developing an new systematic methods to estimate system availability. The main focus areas in this research are to address availability estimation and management through physical asset management, risk-based availability estimation strategies, availability and safety using a failure assessment framework, and availability enhancement using early equipment fault detection and maintenance scheduling optimization.

Irrigation management with remote sensing: Evaluating irrigation requirement for maize under Mediterranean climate condition

tWater use control methods and water resources planning are of high priority. In irrigated agriculture, theright way to save water is to increase water use efficiency through better management. The present workvalidates procedures and methodologies using remote sensing to determine the water availability in thesoil at each moment, giving the opportunity for the application of the water depth strictly necessaryto optimise crop growth (optimum irrigation timing and irrigation amount). The analysis is applied tothe Irrigation District of Divor, Évora, using 7 experimental plots, which are areas irrigated by centre-pivot systems, cultivated to maize. Data were determined from images of the cultivated surface obtainedby satellite and integrated with atmosphere and crop parameters to calculate biophysical indicatorsand indices of water stress in the vegetation—Normalized Difference Vegetation Index (NDVI), Kc, andKcb. Therefore, evapotranspiration (ETc) was estimated and used to calculate crop water requirement,together with the opportunity and the amount of irrigation water to allocate. Although remote sensingdata available from satellite imagery presented some practical constraints, the study could contribute tothe validation of a new methodology that can be used for irrigation management of a large irrigated area,easier and at lower costs than the traditional FAO recommended crop coefficients method. The remotesensing based methodology can also contribute to significant saves of irrigation water.

Acquisition of Vibration Signals for Predictive Maintenance: a Practical Case

As predictive maintenance becomes more and more relevant in industrial environment, the possible range of applications for this maintenance strategy grows. The progresses in components technology and their reduction in price, together with the late years' advances in machine learning and in computational power, are making the implementation of predictive maintenance possible in plants where it would have previously been unreasonably costly. This is leading major pharmaceutical industries to explore the possibility of the application of condition monitoring systems on progressively less and less critical equipment. The focus of this thesis is on the implementation of a system to gather vibrational data from the motors installed in a pre-existing machine using off-the-shelf components. The final goal for the system is to provide the necessary vibration data, in the form of frequency spectra, to a machine learning system developed by IMA Digital, which will be leveraging such data to predict possible upcoming faults and to give the final client all the information necessary to plan maintenance activity according to the estimated machine condition.