Hydraulic systems are complex dynamical systems whose performance can be degraded by certain faults, specifically internal or external leakage. The objective of this research is to develop an appropriate signal processing approach for detection and isolation of these faults. By analyzing the dynamics of the hydraulic actuator, an internal leakage is shown to increase the damping characteristic of the system and change the transient response of the pressure signals. An external leakage, on the other hand, drops the pressure signals without having a significant effect on transient responses. Offline detection of internal leakage in hydraulic actuators is first examined by using fast Fourier, wavelet and Hilbert-Huang transforms. The original pressure signal is decomposed using these transform methods and the frequency component which is sensitive to the internal leakage is identified. The root mean square of the processed pressure signal is used and a comparison of the three transforms is made to assess their ability to detect internal leakage fault, through extensive validation tests. The wavelet transform method is shown to be more suitable for internal leakage detection compared to the other two methods. The wavelet based approach is then extended to an online detection method of internal leakage fault. The online approach considers the more realistic case of an actuator that is driven in a closed-loop mode to track pseudorandom position reference inputs against a load emulated by a spring. Furthermore, the method is shown to remain effective even with control systems which are tolerant to leakage faults. Next, the application of wavelet transform to detect external leakage fault using both offline and online applications in hydraulic actuators is described. The method also examines the isolation of this fault from actuator internal leakage in a multiple-fault environment. The results show that wavelet transform is a fast and easily-implementable method for leakage detection in hydraulic actuators without any need to explicitly incorporate the model of actuator or leakage. Internal leakages as low as 0.124 lit/min, are shown to be detectable, for 80% of the times using structured input signal. For online application, internal leakages in the range of 0.2-0.25 lit/min can be identified. External leakages as low as 0.3 lit/min can be detected in all offline and online applications. Other methods such as observer based and Kalman filter methods, which require the model of the actuator or leakage fault, cannot report leakage detection of magnitudes as low as that reported in this work. The low leak rate detection and not requiring a model of the actuator or leakage make this method very attractive for industrial implementation.

Hydraulic systems are complex dynamical systems whose performance can be degraded by certain faults, specifically internal or external leakage. The objective of this research is to develop an appropriate signal processing approach for detection and isolation of these faults. By analyzing the dynamics of the hydraulic actuator, an internal leakage is shown to increase the damping characteristic of the system and change the transient response of the pressure signals. An external leakage, on the other hand, drops the pressure signals without having a significant effect on transient responses. Offline detection of internal leakage in hydraulic actuators is first examined by using fast Fourier, wavelet and Hilbert-Huang transforms. The original pressure signal is decomposed using these transform methods and the frequency component which is sensitive to the internal leakage is identified. The root mean square of the processed pressure signal is used and a comparison of the three transforms is made to assess their ability to detect internal leakage fault, through extensive validation tests. The wavelet transform method is shown to be more suitable for internal leakage detection compared to the other two methods. The wavelet based approach is then extended to an online detection method of internal leakage fault. The online approach considers the more realistic case of an actuator that is driven in a closed-loop mode to track pseudorandom position reference inputs against a load emulated by a spring. Furthermore, the method is shown to remain effective even with control systems which are tolerant to leakage faults. Next, the application of wavelet transform to detect external leakage fault using both offline and online applications in hydraulic actuators is described. The method also examines the isolation of this fault from actuator internal leakage in a multiple-fault environment. The results show that wavelet transform is a fast and easily-implementable method for leakage detection in hydraulic actuators without any need to explicitly incorporate the model of actuator or leakage. Internal leakages as low as 0.124 lit/min, are shown to be detectable, for 80% of the times using structured input signal. For online application, internal leakages in the range of 0.2-0.25 lit/min can be identified. External leakages as low as 0.3 lit/min can be detected in all offline and online applications. Other methods such as observer based and Kalman filter methods, which require the model of the actuator or leakage fault, cannot report leakage detection of magnitudes as low as that reported in this work. The low leak rate detection and not requiring a model of the actuator or leakage make this method very attractive for industrial implementation.

Compressed air has in the past been considered as a free resource in heavy vehicles.The recent years work to minimize fuel consumption has however made airconsumption an interesting topic for the manufactures to investigate further. Compressed air has many different applications in heavy vehicles. One importantconsumer of compressed air is the brake system, which would not work at allwithout compressed air. The compressed air is produced by a compressor attachedto the engine. A leakage in the system will force the compressor to work longer,which leads to an increased fuel consumption. It is of large interest to have a diagnosis system that can detect leakages, and ifpossible also provide information about where in the system the leakage is present.This information can then be used to repair the leakage at the next service stop. The diagnosis system that is developed in this thesis is based on model baseddiagnosis and uses a recursive least mean square method to estimate the leakagearea. The results from the validation show that the algorithm works well forleakages of the size 1-10 litres/minute. The innovative isolation algorithm givesfull fault isolation for a five circuit system with only three pressure sensors. / Tryckluft i lastbilar har tidigare ansetts vara en fri resurs. Den senaste tidens försökatt minimera bränsleförbrukningen har dock lett fram till att även användandetav tryckluft har börjat ses över. Tryckluft används i dagens lastbilar av flera olika förbrukare. En viktig förbrukareav tryckluft är bromsarna som inte fungerar överhuvudtaget utan tryckluft.Tryckluften produceras av en kompressor som sitter kopplad på förbränningsmotorn.Om det finns ett läckage i tryckluftsystemet leder detta till att kompressornmåste arbeta oftare vilket i sin tur leder till en ökad bränsleförbrukning. Det finns stort intresse av att kunna detektera dessa läckage och om möjligtäven avgöra var i systemet som läckaget finns. Informationen kan sedan användasvid nästa servicetillfälle för att laga läckaget. Diagnossystemet som utvecklats i detta examensarbete bygger på modellbaseraddiagnos och använder en rekursiv implementering av minstakvadratmetodenför att skatta läckagets storlek. Resultat från validering av algoritmen visar attdiagnossystemet fungerar bra för läckage i storleksordningen 1-10 liter/minut. Deninnovativa isoleringsalgoritmen ger full felisolerbarhet för ett system med fem kretsarmen bara tre tryckgivare.

Orientadores: Carlos Roberto de Souza Filho, Teodoro Isnard Ribeiro de Almeida / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Geociências / Made available in DSpace on 2018-08-17T04:04:23Z (GMT). No. of bitstreams: 1 Quiterio_GiulianaClariceMercuri_D.pdf: 42396730 bytes, checksum: 61bf622657c16e3ea121d243ff8a79c3 (MD5) Previous issue date: 2010 / Resumo: Essa pesquisa compreende a aplicação de técnicas de sensoriamento remoto (SR) no aprimoramento dos sistemas de detecção indireta de vazamentos de pequeno porte (<1% de pressão e vazão) em dutos de transporte de hidrocarbonetos (HCs). O objetivo geral do estudo foi verificar a possibilidade de detecção de alterações botânicas relacionadas à presença de gasolina (GSL) e diesel (DSL) no solo, através de respostas espectrais de espécies vegetais, no intervalo de 400 a 2500nm do espectro eletromagnético. As espécies abordadas compreendem três grupos distintos, entre os quais uma gramínea (Brachiaria brizantha (BR)), uma leguminosa (Neonotonia wightii (SJ)) e uma espécie de habito arbóreo (Eucalyptus camaldulensis (EUC)). A gramínea e a leguminosa são perenes e têm ampla ocorrência no território nacional. O ensaio foi realizado em casa de vegetação contendo 45 lisímetros, nos quais contaminações controladas e periódicas foram realizadas buscando-se simular, em escala reduzida, o sistema solo-vegetação de locais com vazamentos indetectáveis pelos sistemas usuais de monitoramento. As variáveis analisadas, incluindo altura, massa da matéria seca e fresca da parte aérea e raízes, conteúdo de pigmentos, amido, açúcar total, nutrição mineral da vegetação e fertilidade do solo, foram correlacionadas com as propriedades de refletância das folhas. Os resultados mostraram que as três espécies vegetais apresentaram alterações espectrais e morfo-fisiológicas relacionadas à presença de GSL e DSL no solo, porém, cada qual com volume de HCs e tempo de exposição distintos. A GSL foi o contaminante mais agressivo e as respostas fisiológicas e espectrais nas plantas submetidas a esse hidrocarboneto foram observadas mais precocemente quando comparada àquelas contaminadas por DSL. Entre as culturas estudadas, a SJ mostrou resultados mais significativos e anomalias em sua resposta espectral puderam ser observadas desde a primeira dose de contaminação. Além das alterações espectrais, a forte queda da massa da matéria da parte aérea proporcionou fácil detecção de áreas contaminadas, inclusive por sensores imageadores multiespecrais e, principalmente, hiperespectrais. A BR também apresentou resultados satisfatórios, especialmente com relação às alterações espectrais, que podem ser facilmente detectadas e diferenciadas do background nos lisímetros de controle, sem contaminação. O EUC mostrou ser a espécie mais resistente a contaminação e respostas espectrais evidentes foram observadas somente após a aplicação de quantidades maiores de HCs no solo. As três espécies apresentaram alterações específicas na região do SWIR em resposta à contaminação, correlacionadas com a metabolização de compostos de sacarídeos, podendo-se especificar padrões de estresse correlacionados com a presença dos HCs no solo. Desta forma, a pesquisa contemplou o objetivo de indicar um espécie vegetal mais suscetível à presença de baixas concentrações de HCs no solo e caracterizar espectralmente as alterações decorrente desta contaminação, possibilitando o desenvolvimento de novas técnicas de monitoramento fino da malha dutoviária nacional brasileira, seja através de sensores portáteis, aerotrasnportados ou orbitais. / Abstract: This research involves the application of remote sensing (RS) data and techniques to improve the indirect detection of small leakages (i.e. <1% in pressure and flow) through hydrocarbon pipelines. The overall objective of the study was to investigate the possibility to detect botanical and attuned visible and infrared (400-2500 nm) spectral changes induced by plant growth on soils contaminated with gasoline (GSL) and diesel (DSL). The species addressed include three distinct groups: a grass specie (Brachiaria brizantha (BR)), a leguminous specie (Neonotonia wightii (SJ)) and type of forest tree (Eucalyptus camaldulensis (EUC)). Both the grass and leguminous species are perennials and have a wide occurrence in Brazil. The leakage experiments were conducted in a greenhouse containing 45 lysimeters, where controlled contaminations were carried out periodically. The notion was to simulate a a contaminated soilvegetation system at reduced scale mimicking an underground, small and slow leakage, which is undetectable by the usual monitoring systems. The analyzed variables, including height, mass of dry and fresh shoot and roots, pigment content, starch, total sugar, mineral nutrition of the vegetation and soil fertility, were correlated with the reflectance properties of plant leaves. The results indicated that the three plant species showed spectral and morphophysiological changes related to the presence of GSL and DSL in the soil, however, each with a specific volume of HCs and different exposure time. The GSL proved to be a more aggressive contaminant. Physiological and spectral responses of plants grown under this hydrocarbon were observed earlier when compared to those contaminated by DSL. Among the crops studied, SJ showed results that are more significant. Anomalous spectral response could be observed since the first dose of contamination applied to this leguminous specie. In addition to the spectral changes, the sharp decrease of the mass of shoot matter provided easy detection of contaminated areas. The same detection showed plausible on spectra simulated to the bandwidth of multispectral and mostly hyperspectral imaging sensors. BR also showed satisfactory results, particularly with respect to spectral changes, which can be easily traced and differentiated from the background (i.e., measurements taken on lysimeters containing plants without contamination). The EUC was found to be the specie most resistant to contamination and spectral responses were only evident after the application of larger amounts of HCs in the soil. The three species showed specific changes in the SWIR region in response to HC contamination. Such changes are connected with the metabolism of saccharides compounds, which seem to cause specified stress patterns correlated with the presence of HCs in the soil. Thus, through this research it was possible to indicate plant species most susceptible to indirectly respond to the presence of low concentrations of HCs in soil and spectrally characterize the botanical changes resulting from this contamination. This enables the development of a new and detailed surveillance method for monitoring the Brazilian pipeline networks, either through portable, airborne or orbital sensors. / Doutorado / Geologia e Recursos Naturais / Doutor em Ciências

The thesis deals with the presentation of an overview of the methods used for leak detection set by technical standards. Following the analysis of the pressure records from the pipeline, a new method is proposed, which is based on existing methods and uses the determination of the direction of arrival of the wave directly at the measurement station. The proposed concept was subsequently developed in Matlab, where the ability to detect was also verified. The whole algorithm was then implemented in programmable logic controllers and a suitable communication between them was designed. The entire solution was then tested in terms of functionality.

Cyber security risk has been a problem ever since the appearance of telecommunication and electronic computers. In the recent 30 years, researchers have developed various tools to protect the confidentiality, integrity, and availability of data and programs. However, new challenges are emerging as the amount of data grows rapidly in the big data era. On one hand, attacks are becoming stealthier by concealing their behaviors in massive datasets. One the other hand, it is becoming more and more difficult for existing tools to handle massive datasets with various data types. This thesis presents the attempts to address the challenges and solve different security problems by mining security risks from massive datasets. The attempts are in three aspects: detecting security risks in the enterprise environment, prioritizing security risks of mobile apps and measuring the impact of security risks between websites and mobile apps. First, the thesis presents a framework to detect data leakage in very large content. The framework can be deployed on cloud for enterprise and preserve the privacy of sensitive data. Second, the thesis prioritizes the inter-app communication risks in large-scale Android apps by designing new distributed inter-app communication linking algorithm and performing nearest-neighbor risk analysis. Third, the thesis measures the impact of deep link hijacking risk, which is one type of inter-app communication risks, on 1 million websites and 160 thousand mobile apps. The measurement reveals the failure of Google's attempts to improve the security of deep links. / Ph. D. / Cyber security risk has been a problem ever since the appearance of telecommunication and electronic computers. In the recent 30 years, researchers have developed various tools to prevent sensitive data from being accessed by unauthorized users, protect program and data from being changed by attackers, and make sure program and data to be available whenever needed. However, new challenges are emerging as the amount of data grows rapidly in the big data era. On one hand, attacks are becoming stealthier by concealing their attack behaviors in massive datasets. On the other hand, it is becoming more and more difficult for existing tools to handle massive datasets with various data types. This thesis presents the attempts to address the challenges and solve different security problems by mining security risks from massive datasets. The attempts are in three aspects: detecting security risks in the enterprise environment where massive datasets are involved, prioritizing security risks of mobile apps to make sure the high-risk apps being analyzed first and measuring the impact of security risks within the communication between websites and mobile apps. First, the thesis presents a framework to detect sensitive data leakage in enterprise environment from very large content. The framework can be deployed on cloud for enterprise and avoid the sensitive data being accessed by the semi-honest cloud at the same time. Second, the thesis prioritizes the inter-app communication risks in large-scale Android apps by designing new distributed inter-app communication linking algorithm and performing nearest-neighbor risk analysis. The algorithm runs on a cluster to speed up the computation. The analysis leverages each app’s communication context with all the other apps to prioritize the inter-app communication risks. Third, the thesis measures the impact of mobile deep link hijacking risk on 1 million websites and 160 thousand mobile apps. Mobile deep link hijacking happens when a user clicks a link, which is supposed to be opened by one app but being hijacked by another malicious app. Mobile deep link hijacking is one type of inter-app communication risks between mobile browser and apps. The measurement reveals the failure of Google’s attempts to improve the security of mobile deep links.

Unreliable and unsustainable electricity supply has been experienced in South Africa since 2007. Eskom implemented Demand Side Management (DSM) as a short-term solution to alleviate this problem. Several compressed-air DSM projects were implemented to help reduce the strain on the electrical network. Compressed air is an integral part of production in deep-level mining, and is extensively utilised. Problems are encountered with the effective management and repairing of leaks, since the majority of mines have little to no procedures in place for leak management. Awareness of the condition of the compressed-air system and leaks needed to be created at management level in order to achieve the best results. The purpose of this study is to investigate the effect of proper leak management on compressed-air systems in the mining industry. Peak-clipping DSM projects implemented in the mining industry were used for evaluation of results. Contribution to the sustainability of compressed-air DSM projects savings through successful leak documentation was the prime focus of this study. This was achieved through the development of a Compressed Air Leakage Documentation System (CALDS). This entailed the electronic field-data capture and record keeping of field data, using rugged PDA devices suitable for the extreme environmental conditions encountered in deep-level mining. Report generation on the status of detected leaks created awareness of compressedair- system performance and leak-repair tracking at management level. Audible detection was sufficient for this study, since the focus was on the larger more-severe leaks. Leaks were expressed in monetary terms to indicate the severity. It was found that successful management of leaks could contribute to an increase of as much as 85% in project savings. The results also showed that creating awareness through documentation of leaks, and the effect this has on the system, resulted in regular repairing of these leaks. Sustainability of projects was maintained during an evaluation period of ten months, with projects achieving on average 125% of target savings. The study showed that effective reporting on compressed-air leaks resulted in increased system efficiency and sustainable DSM project savings. It was also seen that leak detection by outsourced companies did not necessarily result in financial savings. When the mine took responsibility for its own leak detection and repairs, significant savings were realised. / Thesis (M.Ing. (Electrical and Electronic Engineering))--North-West University, Potchefstroom Campus, 2011.

Unreliable and unsustainable electricity supply has been experienced in South Africa since 2007. Eskom implemented Demand Side Management (DSM) as a short-term solution to alleviate this problem. Several compressed-air DSM projects were implemented to help reduce the strain on the electrical network. Compressed air is an integral part of production in deep-level mining, and is extensively utilised. Problems are encountered with the effective management and repairing of leaks, since the majority of mines have little to no procedures in place for leak management. Awareness of the condition of the compressed-air system and leaks needed to be created at management level in order to achieve the best results. The purpose of this study is to investigate the effect of proper leak management on compressed-air systems in the mining industry. Peak-clipping DSM projects implemented in the mining industry were used for evaluation of results. Contribution to the sustainability of compressed-air DSM projects savings through successful leak documentation was the prime focus of this study. This was achieved through the development of a Compressed Air Leakage Documentation System (CALDS). This entailed the electronic field-data capture and record keeping of field data, using rugged PDA devices suitable for the extreme environmental conditions encountered in deep-level mining. Report generation on the status of detected leaks created awareness of compressedair- system performance and leak-repair tracking at management level. Audible detection was sufficient for this study, since the focus was on the larger more-severe leaks. Leaks were expressed in monetary terms to indicate the severity. It was found that successful management of leaks could contribute to an increase of as much as 85% in project savings. The results also showed that creating awareness through documentation of leaks, and the effect this has on the system, resulted in regular repairing of these leaks. Sustainability of projects was maintained during an evaluation period of ten months, with projects achieving on average 125% of target savings. The study showed that effective reporting on compressed-air leaks resulted in increased system efficiency and sustainable DSM project savings. It was also seen that leak detection by outsourced companies did not necessarily result in financial savings. When the mine took responsibility for its own leak detection and repairs, significant savings were realised. / Thesis (M.Ing. (Electrical and Electronic Engineering))--North-West University, Potchefstroom Campus, 2011.

Les fuites au travers des ouvrages hydrauliques en remblai sont les signes précurseurs d'un dysfonctionnementdu dispositif d'étanchéité de l'ouvrage pouvant entraîner leur rupture. La détectionprécoce des fuites et leur quanti_cation est donc primordiale.Les méthodes géophysiques et thermométriques à grand rendement apportent des éléments deréponse pour la détection des fuites, le long des ouvrages à long linéaire, mais l'estimation de leurvitesse, nécessaire à l'évaluation de la dangerosité des fuites, n'est pas encore satisfaisante.Cette étude porte sur la détection et quanti_cation des fuites à travers les ouvrages hydrauliquesen remblai soumis à une charge d'eau permanente. Les méthodes proposées exploitent des mesures detempératures naturelles du sol à l'aide de _bres optiques placées sous le talus amont ou aval.Deux modèles de quanti_cation ont été développés et testés sur les données d'un site expérimentalcontrôlé et d'un site réel. Les résultats obtenus concordent avec les mesures de vitesse e_ectuées surles deux sites. / Leakages through embankment dams are early warning signs of a sealing malfunction and couldlead to its breakdown. Early detection of leakages and their quanti_cation is essential.High output geophysical and thermometric methods provide some answers for leakage detectionalong long linear embankment dams, but their velocity estimations necessary to assess the danger ofleakages, is not yet satisfactory.This study focuses on the detection and the quanti_cation of leakages through embankment damsunder hydraulic head. The proposed method use natural temperature measurements from the groundusing optical _ber buried under the upstream or downstream face.Two models of quanti_cation were developed and tested on data from an experimental site and a realsite. Results are consistent with velocity measurements made at both side.

Modern Heavy Duty Vehicles consist of a multitude of components and operate in various conditions. As there is value in goods transported, there is an incentive to avoid unplanned breakdowns. For this, condition based maintenance can be applied.\newline This thesis presents a study comparing the applicability of the data-driven Consensus SelfOrganizing Models (COSMO) method and the model-driven patent series introduced by Fogelstrom, applied on the air processing system for leakage detection on Scania Heavy Duty Vehicles. The comparison of the two methods is done using the Area Under Curve value given by the Receiver Operating Characteristics curves for features in order to reach a verdict.\newline For this purpose, three criteria were investigated. First, the effects of the hyper-parameters were explored to conclude a necessary vehicle fleet size and time period required for COSMO to function. The second experiment regarded whether environmental factors impact the predictability of the method, and finally the effect on the predictability for the case of nonidentical vehicles was determined.\newline The results indicate that the number of representations ought to be at least 60, rather with a larger set of vehicles in the fleet than with a larger window size, and that the vehicles should be close to identical on a component level and be in use in comparable ambient conditions.\newline In cases where the vehicle fleet is heterogeneous, a physical model of each system is preferable as this produces more stable results compared to the COSMO method. / Moderna tunga fordon består av ett stort antal komponenter och används i många olika miljöer. Då värdet för tunga fordon ofta består i hur mycket gods som transporteras uppstår ett incitament till att förebygga oplanerade stopp. Detta görs med fördel med hjälp av tillståndsbaserat underhåll. Denna avhandling undersöker användbarheten av den data-drivna metoden Consensus SelfOrganizing Models (COSMO) kontra en modellbaserad patentserie för att upptäcka läckage på luftsystem i tunga fordon. Metoderna ställs mot varandra med hjälp av Area Under Curve-värdet som kommer från Receiver Operating Characteristics-kurvor från beskrivande signaler. Detta gjordes genom att utvärdera tre kriterier. Dels hur hyperparametrar influerar COSMOmetoden för att avgöra en rimlig storlek på fordonsflottan, dels huruvida omgivningsförhållanden påverkar resultatet och slutligen till vilken grad metoden påverkas av att fordonsflottan inte är identisk. Slutsatsen är att COSMO-metoden med fördel kan användas sålänge antalet representationer överstiger 60 och att fordonen inom flottan är likvärdiga och har använts inom liknande omgivningsförhållanden. Om fordonsflottan är heterogen så föredras en fysisk modell av systemet då detta ger ett mer stabilt resultat jämfört med COSMO-metoden.