Yes / Wind Energy published by John Wiley & Sons Ltd. Maintenance is essential in keeping wind energy assets operating efficiently. With the development of advanced condition monitoring, diagnostics and prognostics, condition-based maintenance has attracted much attention in the offshore wind industry in recent years. This paper models various maintenance activities and their impacts on the degradation and performance of offshore wind turbine components. An integrated maintenance strategy of corrective maintenance, imperfect time-based preventive maintenance and condition-based maintenance is proposed and compared with other traditional maintenance strategies. A maintenance simulation programme is developed to simulate the degradation and maintenance of offshore wind turbines and estimate their performance. A case study on a 10-MW offshore wind turbine (OWT) is presented to analyse the performance of different maintenance strategies. The simulation results reveal that the proposed strategy not only reduces the total maintenance cost but also improves the energy generation by reducing the total downtime and expected energy not supplied. Furthermore, the proposed maintenance strategy is optimised to find the best degradation threshold and balance the trade-off between the use of condition-based maintenance and other maintenance activities. / UK Engineering and Physical Sciences Research Council (EPSRC). Grant Number: EP/P009743/1

O impacto do Homem sobre a Terra, desde a extração intensiva dos recursos da natureza, extinção das espécies, emissões para o ar e água, consumo de energia e água até as mudanças climáticas do planeta, exigem medidas de contenção e preservação do meio ambiente. O futuro da humanidade é questionado e algo deve ser feito. Nesse contexto surge o conceito de desenvolvimento sustentável. Responsável pelo consumo de 40 a 50% da matéria-prima mundial, 12% da água e 40% das emissões de gases de efeito estufa, a indústria da construção possui importante papel na mitigação dos efeitos nocivos para o meio ambiente e capacidade de atingir altos índices de sustentabilidade. Dentro do ciclo de vida de uma edificação, a fase de Operação/Uso provoca grandes consequências ao meio ambiente e oferece grandes oportunidades de redução dos efeitos adversos. Nessa fase as atividades de manutenção predial acabam por ter seu valor reconhecido. As diversas estratégias de manutenção, em especial a manutenção preventiva baseada em condição, colaboram efetivamente para a durabilidade, desempenho e função da edificação e seus sistemas prediais. Procedimentos de manutenção estão associados à baixa qualidade do ar. A manutenção de sistemas de ar condicionado tem especial destaque devido às consequências para a saúde, bem-estar e produtividade dos ocupantes do edifício. / Due to extensive extraction of natures resources, extinction of species, emission of gases into the atmosphere, water and power consumption, to climatic changes of the planet, mankinds impact on earth requires containment and preservation of the environment. The future of humanity is being questioned and something must be done. Responsible for the consumption of 40 to 50% of raw materials worldwide, 12% of water and 40% of emissions of gases into the atmosphere causing the greenhouse effect, the construction industry has an important role in alleviating the adverse impacts on the environment and the ability to achieve high sustainable levels. Within the lifecycle of a building, the phase of operation/use causes significant environmental consequences but also offers opportunities to alleviate adverse effects. In this phase, the value of building maintenance activities has been recognized. The various strategies for maintenance, principally preventive condition- based maintenance should collaborate effectively towards the durability, performance, function and systems of a building. Air-conditioning maintenance procedures are associated with poor air quality. The maintenance of air-conditioning systems has a special significance due to the effects on health, well-being and productivity of the occupants of the building.

In the trends of technical improvements and automatization is it important for companies to keep up with the developments to be competitive on the market. SwePart Transmissions AB is a company that manufacture and develop gearboxes for the currently growing robot arms industry and the main task with this study is to investigate how to apply condition based monitoring on a new gearbox from the company. The work considers vibration analysis and testing new ideas in the oil analysis field. The tests that were performed are based on measuring the difference in impedance or magnetic field due to the increasement of wear. The results of the tests are not clear. This thesis is the beginning of a big project and therefore lies the value of this work in the new ideas and suggestions for further work.

Electrical contacts provide a well-proven solution to switching various loads in a wide variety of applications, such as power distribution, control applications, automotive and telecommunications. However, electrical contacts are known for limited reliability due to degradation effects upon the switching contacts due to arcing and fretting. Essentially, the life of the device may be determined by the limited life of the contacts. Failure to trip, spurious tripping and contact welding can, in critical applications such as control systems for avionics and nuclear power application, cause significant costs due to downtime, as well as safety implications. Prognostics provides a way to assess the remaining useful life (RUL) of a component based on its current state of health and its anticipated future usage and operating conditions. In this thesis, the effects of contact wear on a set of electromagnetic relays used in an avionic power controller is examined, and how contact resistance combined with a prognostic approach, can be used to ascertain the RUL of the device. Two methodologies are presented, firstly a Physics based Model (PbM) of the degradation using the predicted material loss due to arc damage. Secondly a computationally efficient technique using posterior degradation data to form a state space model in real time via a Sliding Window Recursive Least Squares (SWRLS) algorithm. Health monitoring using the presented techniques can provide knowledge of impending failure in high reliability applications where the risks associated with loss-of-functionality are too high to endure. The future states of the systems has been estimated based on a Particle and Kalman-filter projection of the models via a Bayesian framework. Performance of the prognostication health management algorithm during the contacts life has been quantified using performance evaluation metrics. Model predictions have been correlated with experimental data. Prognostic metrics including Prognostic Horizon (PH), alpha-Lamda (α-λ), and Relative Accuracy have been used to assess the performance of the damage proxies and a comparison of the two models made.

The thesis presents a framework for integrating models, simulation, and experimental data to diagnose incipient failure modes and prognosticate the remaining useful life of critical components, with an application to the main transmission of a helicopter. Although the helicopter example is used to illustrate the methodology presented, by appropriately adapting modules, the architecture can be applied to a variety of similar engineering systems. Models of the kind referenced are commonly referred to in the literature as physical or physics-based models. Such models utilize a mathematical description of some of the natural laws that govern system behaviors. The methodology presented considers separately the aspects of diagnosis and prognosis of engineering systems, but a similar generic framework is proposed for both. The methodology is tested and validated through comparison of results to data from experiments carried out on helicopters in operation and a test cell employing a prototypical helicopter gearbox. Two kinds of experiments have been used. The first one retrieved vibration data from several healthy and faulted aircraft transmissions in operation. The second is a seeded-fault damage-progression test providing gearbox vibration data and ground truth data of increasing crack lengths. For both kinds of experiments, vibration data were collected through a number of accelerometers mounted on the frame of the transmission gearbox. The applied architecture consists of modules with such key elements as the modeling of vibration signatures, extraction of descriptive vibratory features, finite element analysis of a gearbox component, and characterization of fracture progression. Contributions of the thesis include: (1) generic model-based fault diagnosis and failure prognosis methodologies, readily applicable to a dynamic large-scale mechanical system; (2) the characterization of the vibration signals of a class of complex rotary systems through model-based techniques; (3) a reverse engineering approach for fault identification using simulated vibration data; (4) the utilization of models of a faulted planetary gear transmission to classify descriptive system parameters either as fault-sensitive or fault-insensitive; and (5) guidelines for the integration of the model-based diagnosis and prognosis architectures into prognostic algorithms aimed at determining the remaining useful life of failing components.

Condition-Based Maintenance (CBM) and Prognostics and Health Management (PHM) technologies aim at improving the availability, reliability, maintainability, and safety of systems through the development of fault diagnostic and failure prognostic algorithms. In complex engineering systems, such as aircraft, power plants, etc., the prognostic activities have been limited to the component-level, primarily due to the complexity of large-scale engineering systems. However, the output of these prognostic algorithms can be practically useful for the system managers, operators, or maintenance personnel, only if it helps them in making decisions, which are based on system-level parameters. Therefore, there is an emerging need to build health assessment methodologies at the system-level. This research employs techniques from the field of design-of-experiments to build response surface metamodels at the system-level that are built on the foundations provided by component-level damage models.

Prognostics and health management (PHM) is a major tool enabling systems to evaluate their reliability in real-time operation. Despite ground-breaking advances in most engineering and scientific disciplines during the past decades, reliability engineering has not seen significant breakthroughs or noticeable advances. Therefore, self-awareness of the embedded system is also often required in the sense that the system should be able to assess its own health state and failure records, and those of its main components, and take action appropriately. This thesis presents a radically new prognostics approach to reliable system design that will revolutionise complex power electronic systems with robust prognostics capability enhanced Insulated Gate Bipolar Transistors (IGBT) in applications where reliability is significantly challenging and critical. The IGBT is considered as one of the components that is mainly damaged in converters and experiences a number of failure mechanisms, such as bond wire lift off, die attached solder crack, loose gate control voltage, etc. The resulting effects mentioned are complex. For instance, solder crack growth results in increasing the IGBT’s thermal junction which becomes a source of heat turns to wire bond lift off. As a result, the indication of this failure can be seen often in increasing on-state resistance relating to the voltage drop between on-state collector-emitter. On the other hand, hot carrier injection is increased due to electrical stress. Additionally, IGBTs are components that mainly work under high stress, temperature and power consumptions due to the higher range of load that these devices need to switch. This accelerates the degradation mechanism in the power switches in discrete fashion till reaches failure state which fail after several hundred cycles. To this end, exploiting failure mechanism knowledge of IGBTs and identifying failure parameter indication are background information of developing failure model and prognostics algorithm to calculate remaining useful life (RUL) along with ±10% confidence bounds. A number of various prognostics models have been developed for forecasting time to failure of IGBTs and the performance of the presented estimation models has been evaluated based on two different evaluation metrics. The results show significant improvement in health monitoring capability for power switches. Furthermore, the reliability of the power switch was calculated and conducted to fully describe health state of the converter and reconfigure the control parameter using adaptive algorithm under degradation and load mission limitation. As a result, the life expectancy of devices has been increased. These all allow condition-monitoring facilities to minimise stress levels and predict future failure which greatly reduces the likelihood of power switch failures in the first place.

O impacto do Homem sobre a Terra, desde a extração intensiva dos recursos da natureza, extinção das espécies, emissões para o ar e água, consumo de energia e água até as mudanças climáticas do planeta, exigem medidas de contenção e preservação do meio ambiente. O futuro da humanidade é questionado e algo deve ser feito. Nesse contexto surge o conceito de desenvolvimento sustentável. Responsável pelo consumo de 40 a 50% da matéria-prima mundial, 12% da água e 40% das emissões de gases de efeito estufa, a indústria da construção possui importante papel na mitigação dos efeitos nocivos para o meio ambiente e capacidade de atingir altos índices de sustentabilidade. Dentro do ciclo de vida de uma edificação, a fase de Operação/Uso provoca grandes consequências ao meio ambiente e oferece grandes oportunidades de redução dos efeitos adversos. Nessa fase as atividades de manutenção predial acabam por ter seu valor reconhecido. As diversas estratégias de manutenção, em especial a manutenção preventiva baseada em condição, colaboram efetivamente para a durabilidade, desempenho e função da edificação e seus sistemas prediais. Procedimentos de manutenção estão associados à baixa qualidade do ar. A manutenção de sistemas de ar condicionado tem especial destaque devido às consequências para a saúde, bem-estar e produtividade dos ocupantes do edifício. / Due to extensive extraction of natures resources, extinction of species, emission of gases into the atmosphere, water and power consumption, to climatic changes of the planet, mankinds impact on earth requires containment and preservation of the environment. The future of humanity is being questioned and something must be done. Responsible for the consumption of 40 to 50% of raw materials worldwide, 12% of water and 40% of emissions of gases into the atmosphere causing the greenhouse effect, the construction industry has an important role in alleviating the adverse impacts on the environment and the ability to achieve high sustainable levels. Within the lifecycle of a building, the phase of operation/use causes significant environmental consequences but also offers opportunities to alleviate adverse effects. In this phase, the value of building maintenance activities has been recognized. The various strategies for maintenance, principally preventive condition- based maintenance should collaborate effectively towards the durability, performance, function and systems of a building. Air-conditioning maintenance procedures are associated with poor air quality. The maintenance of air-conditioning systems has a special significance due to the effects on health, well-being and productivity of the occupants of the building.

Samarbetspartnern som denna studie har gjorts för har som mål att konstruera en detektor för tågtrafiken som bygger på bildigenkänning och artificiell intelligens. Problemet är att de lösningar som finns idag är dyra, och därför är en förutsättning att den ska vara byggd med konsumentprodukter för att få ner kostnaden samt att den ska vara enkel att installera och underhålla. Flera ramverk för objektigenkänning existerar, men dessa bygger på olika metoder och tekniker. Studien har därför utförts som en fallstudie vars syfte har varit att jämföra två välanvända ramverk för objektigenkänning för att identifiera olika för- och nackdelar gällande noggrannhet och tidsåtgång vid träning och test med hjälp av dessa ramverk. Även vilka olika utmaningar som stötts på under tillvägagångssättet har lyfts fram. Studien sammanfattar sedan dessa för att skapa idéer och diskussion för hur dessa skulle kunna implementeras på den nya tågdetektorn. Ramverken som har jämförts är OpenCV och Google TensorFlow. Dessa bygger på olika objektigenkänningstekniker, i huvudsak kaskadklassificering och neurala nät. Ramverken testades med en datamängd på 400 bilder på olika tågfordon där hjulaxlarna användes som parameter för objektigenkänningen. Testerna bedömdes efter kriterier gällande noggrannhet, tidsåtgång för träning samt komplexitet för konfiguration och användning. Resultatet visade att OpenCV hade en snabb träningsprocess, men visade låg precision och en mer komplex konfigurerings- och användningsprocess. TensorFlow hade en långsammare träningsprocess, men visade istället bättre precision och en mindre komplex konfigurering. Slutsatsen av studien är att TensorFlow visade bäst resultat och har mest potential att användas i den nya tågdetektorn. Detta baseras på studiens resultat samt att den bygger på modernare tekniker med neurala nät för objektigenkänning. / The research in this thesis is conducted with the partners aim to construct a new train detection system that uses image recognition and artificial intelligence. Detectors like these that exists today are expensive, so the construction is going to be based around the use of consumer electronics to lower the cost and simplify installation and maintenance. Several frameworks for object detection are available, but they use different approaches and methods. This thesis is therefore carried out as a case study that compares two widely used frameworks for image recognition tasks. The purpose is to identify advantages and disadvantages regarding training and testing when using these frameworks. Also highlighted is different challenges encountered in the process. The summary of the results is used to form ideas and a discussion about how to implement a framework in the new detection system. The frameworks compared in this study are OpenCV and Google TensorFlow. These frameworks use different methods for object detection, mainly cascade classifiers and convolutional neural nets. The frameworks were tested using a dataset of 400 images on different trains where the wheel-axles were used as the object of interest. The results were analyzed based on criteria regarding precision, total training time and also complexity regarding configuration and usage. The results showed that OpenCV had a faster training process but had low precision and more complex configuration. TensorFlow had a much longer training process but had better precision and less complex configuration. The conclusion of the study is that TensorFlow overall showed the best result and has a better potential for implementation in the new detection system. This is based on the results from the study, but also that the framework is developed with a more modern approach using convolutional neural nets for bject detection.

Ett transformatorfel kan få stora ekonomiska konsekvenser och påverka ett elkraftsystems driftsäkerhet. Genom att övervaka en transformators tillstånd kan haverier och avbrott undvikas. Tillståndsövervakning möjliggör även att förebyggande underhåll kan planeras effektivt. Det här arbetet har undersökt tillgängliga diagnostikmetoder och övervakningstekniker för tillståndsbedömning av transformatorer.  Tillgänglig felstatistik för transformatorer har studerats ingående för att förstå vilka fel som kan uppstå i en transformator och i vilken grad de förekommer. Eftersom felen har olika konsekvenser för transformatorns fortsatta drift har dessa undersökts. Befintliga metoder för att upptäcka fel har dokumenterats. Detta har utförts genom att studera tillgänglig litteratur och via intervjuer med företag som tillverkar övervakningsutrustning för transformatorer. Övervakningsmetoderna har jämförts med avseende på kostnad, livslängd och noggrannhet. Utifrån dessa analyser har en rekommendation tagits fram över vilka övervakningsmetoder som är mest lämpade för Svenska Kraftnät. Det finns verktyg för att kvantifiera resultaten från övervakningsmetoder till lättolkad information. Ett sådant är hälsoindexet, som komprimerar data från olika mätningar, till ett enskilt värde som representerar en komponents tillstånd. En fallstudie har utförts där tre transformatorers tillstånd under perioden 2002–2015 har undersökts med ett befintligt hälsoindex. Resultatet visar att hälsoindex kan utnyttjas för att indikera transformatorernas tillstånd. Nackdelen med hälsoindexet som användes är att indexet är fortsatt högt oavsett kvaliteten på isolationsmaterialet. Därför föreslås en alternativ modell för en hälsoindexberäkning, i vilken pappersåldringen beaktas i större utsträckning. / A transformer fault could affect the reliability of a power system and have serious economic consequences. Therefore there is an increasing demand among electrical utilities to assess the actual condition of their transformers and hence detect faults before they occur. Condition monitoring has the potential to reduce operating costs and improve the reliability of operation. The aim of this master thesis has been to investigate available diagnostic measurement techniques that can assess the condition of power transformers. Transformer failure statistics has been studied in order to understand what different faults that can occur and to which extent they appear. The consequences of different faults have been investigated. Available measurement techniques were coupled with what faults they can detect. The diagnostic measurement techniques have also been compared in regard to cost, lifetime and accuracy. The comparison resulted in a recommendation over which measurement techniques that are most suitable for the Swedish transmission system operator, Svenska Kraftnät. There is a need among electrical utilities of economic and technical justifications for optimal investment and maintenance decisions. One available asset management technique that enables this is the health index. A health index is a tool that combines available measurement data from operating observations, field inspections and laboratory testing into an objective and quantitative index. The index provides information about the overall condition of an asset. A case study has been conducted where an available health index was used to estimate the condition of three transformers. The results indicate that the health index presents an efficient way to represent the condition of transformers. The disadvantage of the used index is that it implies a good condition even when the quality of the transformer insulation paper is poor. An alternative health index is therefore proposed where the paper insulation quality has a larger impact on the index.