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.

Observations of Acoustic Emission in Power Semiconductors

Industrial, electrical power generation, and transportation systems, to name but a few, rely heavily on power electronics to control and convert electrical power. Each of these systems, when encountering an unexpected failure, can cause significant financial losses, or even an emergency. A condition monitoring system would help to alleviate these concerns, but for the time being, there is no generally accepted and widely adopted method for power electronics. Acoustic emission is used as a failure precursor in many applications, but it has not been studied in power electronics so far. In this doctoral dissertation, observations of acoustic emission in power semiconductor components are presented. The acoustic emissions are caused by the switching operation and failure of power transistors. Three types of acoustic emission are observed. Furthermore, aspects related to the measurement and detection of acoustic phenomena are discussed. These include sensor performance and mechanical construction of experimental setups. The results presented in this dissertation are the outset of a research program where it will be determined whether an acoustic-emission-based condition monitoring method can be developed.

Developing asset management in district heating and cooling business in a large energy company

The purpose of this Master´s Thesis is to develop asset management and its practices in case company. District heating and cooling systems operated by case company around Finland, Sweden, Poland and the Baltics form an enormous-sized asset base where some parts are starting to reach their end of life-cycles. Large-sized asset renewal actions are under discussion and maintenance spending is increasing. Financially justified decisions in changing business environment are needed. Asset management is one of the most important concepts for production organization which operates with capital-intensive production assets. Organizations profitability is highly dependent on assets´ performance. Such assets, like district heating and cooling systems, should be utilized as efficiently as possible within their life-cycles but also maintained and renewed optimally. In this qualitative thesis, empirical interview study was conducted to describe the current situation on how the assets are managed in the case company and to examine the readiness to implement a new, risk-based solution. Asset management revealed to be a very well-known concept. From proposed risk-based asset management point of view, several key observations were made. It was seen as a suitable solution, but further development will be needed. Based on the need and findings, several key processes and frameworks were created and also tested with a case study. Assets` condition monitoring should be improved, which would have a positive impact on event probability assessment. Risk acceptance is also a thing to be discussed further. When the evaluation becomes fluent in single investment cases, portfolio-level expansion should be considered and started. As a result, thesis proposes a solution how risk-based asset management could be performed practically in a capital-intensive case company in order to optimize the maintenance spending in a long run. Created practical framework is made universal: similar principles can be applied into multiple cases in case company but also in other energy companies. Risk-based asset management`s benefits could be utilized best in portfolio-level optimization where the capital would be invested to the most important objects from total risk point of view. Eventually, such approach would allow case company to optimize capital spending in a situation where funds are not adequate to cover all the mandatory needs and prioritization between the investment alternatives will truly be needed.

Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.

Redes neurais artificiais aplicadas à manutenção baseada na condição

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Ingegneria di Manutenzione

Lo scopo di questa tesi di dottorato di ricerca consiste nel fornire la giusta collocazione della manutenzione fra le discipline dell'ingegneria, raccogliendo e formalizzando le metodologie di analisi di affidabilità e di pianificazione degli interventi all'interno di un unico processo di progettazione e di controllo. In linea di principio, un processo di analisi dei guasti e di programmazione della manutenzione deve essere in grado di fornire chiare e sicure risposte ai seguenti interrogativi: Quali sono le funzioni richieste e con quali criteri di prestazioni il sistema è chiamato ad assolverle? Qual'è l'andamento della disponibilità del sistema in funzione del tempo? Quanti guasti e di quale tipo si possono verificare durante la vita del sistema? Quali possono essere le conseguenze che ledono la sicurezza e la protezione ambientale? Quanti pezzi di ricambio sono necessari? Che tipo di interventi di manutenzione preventiva risultano tecnicamente fattibili? A quali scadenze devono essere programmati? A quanto ammonta la previsione del costo di esercizio del sistema? Quante squadre di manutenzione devono essere assegnate al sistema? Come deve essere organizzata la logistica di manutenzione? Con quali tecniche si prevede di riconoscere i guasti e quali procedure devono essere attivate per farvi fronte? E' possibile implementare tecniche di `condition monitoring' delle macchine? Su quali tempi di preavviso sui guasti si può contare? In tal senso, la manutenzione necessita delle tecniche e degli opportuni strumenti che siano in grado di misurarne l'efficacia e l'efficienza. L'efficacia in primo luogo, in quanto l'obiettivo principe consiste nel garantire che il sistema oggetto di studio continui a svolgere le proprie funzioni nei limiti di prestazioni accettabili, secondo le specifiche richieste degli utilizzatori. L'efficienza in secondo luogo, ma non per questo di minore importanza, in quanto perseguendo l'obiettivo di cui sopra, occorre impegnare il minimo di risorse possibili, organizzando con razionalità il supporto logistico del sistema al fine di raggiungere i massimi livelli di rendimento di gestione. La migliore strategia di manutenzione può essere pianificata, a priori, solo se si è in grado di prevedere con la necessaria precisione l'evoluzione del sistema nel suo contesto operativo futuro. E' allora possibile formulare un modello matematico del sistema, studiarne la dinamica ed osservare le reazioni alla simulazione di eventuali stimoli esterni. I metodi ed i modelli noti dell'ingegneria dei sistemi possono essere molto utili per la risoluzione di casi semplici, ma sovente richiedono la formulazione di ipotesi troppo restrittive che aumentano in modo inaccettabile la distanza del modello dalla realtà. Una strada alternativa ed affascinante, che ho percorso con entusiasmo durante questi tre anni di studi e ricerca, consiste nella simulazione numerica della vita del sistema, utilizzando il metodo Monte Carlo per la gestione dei processi stocastici di guasto e per l'esecuzione degli interventi di manutenzione. Ho quindi messo a punto il codice di simulazione RAMSES, perseguendo l'idea di costruire uno strumento di misura dell'efficacia e dell'efficienza di una politica di manutenzione simulata al calcolatore. Nella tesi si presentano i concetti di base dell'ingegneria dei sistemi applicata al caso della manutenzione e si introduce il formalismo della Reliability Centred Maintenance come miglior guida nella pianificazione delle schede di manutenzione. Si introducono le nozioni di base per fornire una struttura solida e corretta alla simulazione numerica dei sistemi riparabili e si presenta il codice RAMSES corredando le informazioni tecniche con i dovuti esempi ed applicazioni pratiche. Si conclude il lavoro, infine, con la presentazione di un modello di massima verosimiglianza particolarmente utile per le analisi dei dati sperimentali di guasto dei componenti.

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.

Aging of nuclear power plant cables: in search of non-destructive diagnostic quantities

The safety systems of nuclear power plants rely on low-voltage power, instrumentation and control cables. Inside the containment area, cables operate in harsh environments, characterized by relatively high temperature and gamma-irradiation. As these cables are related to fundamental safety systems, they must be able to withstand unexpected accident conditions and, therefore, their condition assessment is of utmost importance as plants age and lifetime extensions are required. Nowadays, the integrity and functionality of these cables are monitored mainly through destructive test which requires specific laboratory. The investigation of electrical aging markers which can provide information about the state of the cable by non-destructive testing methods would improve significantly the present diagnostic techniques. This work has been made within the framework of the ADVANCE (Aging Diagnostic and Prognostics of Low-Voltage I\&C Cables) project, a FP7 European program. This Ph.D. thesis aims at studying the impact of aging on cable electrical parameters, in order to understand the evolution of the electrical properties associated with cable degradation. The identification of suitable aging markers requires the comparison of the electrical property variation with the physical/chemical degradation mechanisms of polymers for different insulating materials and compositions. The feasibility of non-destructive electrical condition monitoring techniques as potential substitutes for destructive methods will be finally discussed studying the correlation between electrical and mechanical properties. In this work, the electrical properties of cable insulators are monitored and characterized mainly by dielectric spectroscopy, polarization/depolarization current analysis and space charge distribution. Among these techniques, dielectric spectroscopy showed the most promising results; by means of dielectric spectroscopy it is possible to identify the frequency range where the properties are more sensitive to aging. In particular, the imaginary part of permittivity at high frequency, which is related to oxidation, has been identified as the most suitable aging marker based on electrical quantities.

Beitrag einer nutzungsabhängigen Instandhaltung zur Planung von Leistungsverfügbarkeit

Stets darauf bedacht, die Anlagen- und Maschinenverfügbarkeit bei möglichst geringem Ressourceneinsatz zu gewährleisten, wird die Rolle der Instandhaltung als unternehmerischer Wertschöpfungsfaktor immer bedeutsamer. Voraussetzung für eine Nutzbarmachung bestehender Potentiale sind neue Werkzeuge und Ansätze, deren Umsetzung eine effiziente Sicherstellung von Verfügbarkeit ermöglicht. Vor diesem Hintergrund wurde im Teilprojekt C3 des DFG Paketantrags 672 ein Konzept zur nutzungsabhängigen Instandhaltung entwickelt. Auf Grundlage des bestehenden Zusammenhangs von Nutzung und Abnutzung risikobehafteter Bauteile intralogistischer Systeme können damit die durch zukünftige Systemlasten hervorgerufenen Beanspruchungen antizipiert werden. Instandhaltungsmaßnahmen und technische Verfügbarkeiten werden dadurch anforderungsgerecht und ressourcen-optimal planbar.

Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.

Fibre-based devices for next generation photonics communication systems

The future broadband information network will undoubtedly integrate the mobility and flexibility of wireless access systems with the huge bandwidth capacity of photonics solutions to enable a communication system capable of handling the anticipated demand for interactive services. Towards wide coverage and low cost implementations of such broadband wireless photonics communication networks, various aspects of the enabling technologies are continuingly generating intense research interest. Among the core technologies, the optical generation and distribution of radio frequency signals over fibres, and the fibre optic signal processing of optical and radio frequency signals, have been the subjects for study in this thesis. Based on the intrinsic properties of single-mode optical fibres, and in conjunction with the concepts of optical fibre delay line filters and fibre Bragg gratings, a number of novel fibre-based devices, potentially suitable for applications in the future wireless photonics communication systems, have been realised. Special single-mode fibres, namely, the high birefringence (Hi-Bi) fibre and the Er/Yb doped fibre have been employed so as to exploit their merits to achieve practical and cost-effective all-fibre architectures. A number of fibre-based complex signal processors for optical and radio frequencies using novel Hi-Bi fibre delay line filter architectures have been illustrated. In particular, operations such as multichannel flattop bandpass filtering, simultaneous complementary outputs and bidirectional nonreciprocal wavelength interleaving, have been demonstrated. The proposed configurations featured greatly reduced environmental sensitivity typical of coherent fibre delay line filter schemes, reconfigurable transfer functions, negligible chromatic dispersions, and ease of implementation, not easily achievable based on other techniques. A number of unique fibre grating devices for signal filtering and fibre laser applications have been realised. The concept of the superimposed fibre Bragg gratings has been extended to non-uniform grating structures and into Hi-Bi fibres to achieve highly useful grating devices such as overwritten phase-shifted fibre grating structure and widely/narrowly spaced polarization-discriminating filters that are not limited by the intrinsic fibre properties. In terms of the-fibre-based optical millimetre wave transmitters, unique approaches based on fibre laser configurations have been proposed and demonstrated. The ability of the dual-mode distributed feedback (DFB) fibre lasers to generate high spectral purity, narrow linewidth heterodyne signals without complex feedback mechanisms has been illustrated. A novel co-located dual DFB fibre laser configuration, based on the proposed superimposed phase-shifted fibre grating structure, has been further realised with highly desired operation characteristics without the need for costly high frequency synthesizers and complex feedback controls. Lastly, a novel cavity mode condition monitoring and optimisation scheme for short length, linear-cavity fibre lasers has been proposed and achieved. Based on the concept and simplicity of the superimposed fibre laser cavities structure, in conjunction with feedback controls, enhanced output performances from the fibre lasers have been achieved. The importance of such cavity mode assessment and feedback control for optimised fibre laser output performance has been illustrated.

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.

A facilities maintenance management process based on degradation prediction using sensed data

Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.