Thesis (MScEng)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: Fault detection and isolation (FDI) is an important aspect of effective fault tolerant control architectures. The Electronic System Laboratory at Stellenbosch University identified the need to study viable methods of FDI. In this research two FDI methods for actuator failures on the Meraka Modular UAV are investigated. The Meraka Modular UAV is an unmanned aircraft that was developed by the CSIR. A simple six degree of freedom non-linear mathematical model is developed that presents a platform on which the two FDI methods are formulated. The theoretical model is used in a simulation environment to extensively test and compare the performance of the proposed FDI methods in different types of flight conditions. The first method investigated is a multiple model adaptive estimator (MMAE), which incorporates a bank of Kalman filters. Each Kalman filter in the MMAE is conditioned for each expected actuator fault scenario. The limitations of using linear Kalman filters are explained and they are replaced by extended Kalman filters, whose associated advantages and disadvantages are discussed. Each filter in the bank of Kalman filters produces a residual vector and residual covariance matrix. This information is subjected to a Bayes classifier to determine the fault scenario which will have the highest likelihood of being active. The second method that is studied incorporates the parity space approach for FDI. The parity space consists of the parity relations that quantify all the analytical redundancies available between the sensors’ outputs and actuator inputs of a system. A transformation matrix is then optimised to transform these parity relations into residuals that are specially sensitive to specific actuator faults. Actuator faults cause the parity space residuals’ variance to increase. A cumulative summation procedure is used to determine when the residuals’ variance has changed sufficiently to indicate an actuator fault. A pseudoinverse actuator estimation scheme is used to extract the actuator deflections from the parity relations. The FDI performance is tested by deliberately failing specific actuators of the Meraka Modular UAV in-flight. The flight test data is then used to analyse and compare the performance of the two FDI methods investigated in the research. It is found that, for the specific Meraka Modular UAV, the FDI performs as expected with disturbance effects and actuator excitation influencing the FDI effectiveness. The research shows that the bank of Kalman filters creates less false alarms whereas the parity space FDI is more sensitive to faults. It is illustrated that FDI can be improved with active actuator excitation and process noise estimation techniques, delivering promising results. / AFRIKAANSE OPSOMMING: Fout-deteksie en -isolasie (FDI) is belangrik vir ’n stelsel se beheerder om foute te kan hanteer. Die Elektroniese Stelsellabaratorium (ESL) by die Universiteit van Stellenbosch het die behoefte geïdentifiseer om te gaan kyk na moontlike FDI-stelsels wat gebruik kan word op hul onbemande vliegtuie (OV). In hierdie navorsing is daar na twee FDI-metodes gekyk wat op die Meraka Modulêre OV toegepas kan word. Die Meraka Modulêre OV is ’n vliegtuig wat deur die WNNR ontwikkel is. ’n Eenvoudige sesgrade- van-vryheid, nie-liniêre wiskundige model van die Meraka Modulêre OV is ontwikkel, en die FDI-metodes is rondom hierdie model geformuleer. Die teoretiese model is gebruik in ’n simulasie-omgewing en die werkverrigting van die twee FDI-metodes is in verskillende vlug-omstandighede getoets en vergelyk. Die eerste metode waarna gekyk is, was ’n multi-model aanpasbare afskatter (MMAA), wat ’n bank van Kalman-filters gebruik. Elke Kalman-filter in die MMAA is gekondisioneer vir elke denkbare aktueerder-fout. Die beperkinge rondom liniêre Kalman-filters is uitgelig en vergelyk met uitgebreide Kalman-filters, waarvan die voor- en nadele bespreek is. Elke filter in die MMAA produseer ’n residu-vektor en residu-kovariansiematriks. Hierdie informasie is na ’n Bayes-klassifiseerder gestuur om te bepaal watter fout-senario die grootste waarskynlikheid het om aktief te wees. Die tweede metode waarna gekyk is, het die pariteitsruimte vir FDI gebruik. Die pariteitsruimte is uit al die pariteitsverwantskappe opgebou wat die verhoudings tussen al die insette en uitsette van ’n sisteem kwantifiseer. ’n Transformasie-matriks is geoptimaliseer om hierdie pariteitsverwantskappe te transformeer na residue wat elkeen sensitief is tot ’n spesikiefe aktueerderfout. ’n Spesifieke aktueerderfout veroorsaak dat ’n spesifieke residu se variansie verhoog. ’n Kummulatiewe sommeringsproses is dan gebruik om te bepaal of die variansie genoegsaam toegeneem het. Sodoende kon daar bepaal word of ’n fout ontstaan het. ’n Pseudo-inversaktueerder-afskattingstegniek is gebruik om die afgeskatte aktueerderdefleksie uit die pariteitsverwantskappe te onttrek. Die FDI-werkverrigtinge van die twee metodes is getoets deur sekere aktueerders met opset te laat faal gedurende vlugtoetse. Die vlugtoetsdata is gebruik om die werkverrigting van die FDI-metodes te analiseer en met mekaar te vergelyk. Met die spesifieke Meraka Modulêre OV is, soos te wagte, bevind dat versteurings en aktueerderopwekking ’n groot invloed op die FDI’s se werkverrigtinge toon.

abstract: This thesis provides a cost to benefit assessment of the proposed next generation distribution system, the Future Renewable Electric Energy Distribution Management (FREEDM) system. In this thesis, a probabilistic study is conducted to determine the payback period for an investment made in the FREEDM distribution system. The stochastic study will help in performing a detailed analysis in estimating the probability density function and statistics associated with the payback period. This thesis also identifies several parameters associated with the FREEDM system, which are used in the cost benefit study to evaluate the investment and several direct and indirect benefits. Different topologies are selected to represent the FREEDM test bed. Considering the cost of high speed fault isolation devices, the topology design is selected based on the minimum number of fault isolation devices constrained by enhanced reliability. A case study is also performed to assess the economic impact of energy storage devices in the solid state transformers so that the fault isolation devices may be replaced by conventional circuit breakers. A reliability study is conducted on the FREEDM distribution system to examine the customer centric reliability index, System Average Interruption Frequency Index (SAIFI). It is observed that the SAIFI was close to 0.125 for the FREEDM distribution system. In addition, a comparison study is performed based on the SAIFI for a representative U.S. distribution system and the FREEDM distribution system. The payback period is also determined by adopting a theoretical approach and the results are compared with the Monte Carlo simulation outcomes to understand the variation in the payback period. It is observed that the payback period is close to 60 years but if an annual rebate is considered, the payback period reduces to 20 years. This shows that the FREEDM system has a significant potential which cannot be overlooked. Several direct and indirect benefits arising from the FREEDM system have also been discussed in this thesis. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2016

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Ce mémoire de thèse présente une étude fondamentale enrichie par des contributions qui sont articulées autour de la modélisation de processus ainsi qu'un diagnostic de défauts en utilisant l'analyse en composantes principales (ACP). Dans l'objectif d'un choix optimal du modèle ACP, une étude comparative de quelques critères connus dans la littérature nous a permis de conclure que le problème rencontré est souvent lié à une ignorance des variables indépendantes et quasi-indépendantes. Dans ce cadre, nous avons réalisé deux démonstrations mettant en évidence les limitations de deux critères en particulier la variance non reconstruite (VNR). En s'appuyant sur le principe d'une telle variance, nous avons proposé trois nouveaux critères. Parmi eux, deux ont été considérés comme étant empiriques car seule l'expérience permettra de prouver leur efficacité. Le troisième critère noté VNRVI représente un remède à la limitation du critère VNR. Une étude de sa consistance théorique a permis d'établir les conditions garantissant l'optimalité de son choix. Les résultats de simulation ont validé une telle théorie en prouvant ainsi que le critère VNRVI étant plus efficace que ceux étudiés dans cette thèse. Dans le cadre d'un diagnostic de défauts par ACP, l'approche de reconstruction des indices de détection ainsi que celle des contributions ont été utilisées. A travers une étude de généralisation, nous avons étendu le concept d'isolabilité de défauts par reconstruction à tout indice quadratique. / This thesis presents a fundamental study enhanced by some contributions that are focused on process modelling and fault diagnosis using principal components analysis (PCA). In order to find an optimal PCA model, we have concluded through a comparative study of some popular criteria that the problem is often related to an ignorance of the independent and quasi-independent variables. In this framework, we have performed two demonstrations highlighting the limitations of two selection criteria in particular the unreconstructed variance (VNR). Based on the principle of VNR approach, we have proposed three new criteria, among them two methods were considered as empirical criteria because only the experience will prove their effectiveness. However the third one which is noted VNRVI represents a cure for the limitation of the classical VNR criterion. Thus, the conditions that ensure an optimal selection were derived according to a theoretical consistency study of the VNRVI approach. The simulation results have successfully validated the VNRVI criterion by proving that is more effective than the other studied criteria in the present thesis. The reconstruction and contributions approaches were used for fault diagnosis using PCA. According to a unified study, we have extended the fault isolability concept based on the reconstruction method to any detection index which has a quadratic form. Such generalization has allowed us to develop a theoretical fault isolability analysis based on the reconstruction of the combined index versus those of SPE and T2 indices. This analysis has highlighted the advantage of using the combined index for fault isolation.

La disponibilité de certains capteurs est indispensable pour le contrôle des machines électriques dans une application automobile. Cette thèse constitue une contribution à l'étude d'une commande tolérante aux défauts pour un entraînement électrique dans le cadre du projet SOFRACI. Pour pallier une défaillance de ces capteurs, des stratégies sont mises en place pour assurer une continuité de fonctionnement ou un arrêt sûr. Dans le cas de la machine synchrone, les capteurs les plus critiques sont: le capteur de position, les capteurs de courant et le capteur de bus de tension continue. C'est dans ce contexte que l'on a développé des algorithmes de commande tolérante aux défauts avec successivement des étapes de détection, d'isolation et de reconfiguration. Ensuite, la validation expérimentale a été effectuée sur un banc composé d’une machine synchrone et d’un onduleur avec 3 ponts H conçus pour la propulsion d’un véhicule électrique. Ainsi les méthodes développées et qui s’appuient principalement sur la théorie du contrôle, sont évaluées expérimentalement à travers des injections de défauts en temps réel, avec un accent mis sur le temps nécessaire à la détection. / During the last decade, Fault Tolerant Control (FTC) has become an increasingly interesting topic in automotive industry. The operation of electrical drives is highly dependent on feedback sensors availability. With the aim of reaching the required level of availability in transportation applications, the drive is equipped with a DC voltage sensor, three current sensors (due to safety requirements in electric vehicle standards) and a position sensor. This PhD is a contribution to the study of an electrical drive fault tolerant control. The objective is to have a system, which can adaptively reorganizes itself at a sensor failure occurrence. Consequently, strategies are defined from the early preliminary design steps, so as to facilitate fault detection, fault isolation and control reconfiguration. To this purpose, our work goes from theoretical studies toward experimental validations through the model simulation using control theory.In this thesis, FTC algorithms are developed for the rotor position, the phase currents and DC link voltage sensors. The experimentally validation is perform with an electrical drive composed of a Permanent Magnet Synchronous Machine and a 3H bridge inverter. Thus, the developed methods are evaluated experimentally through real time fault injection, with an emphasis on the detection time.

<p>This master thesis report discusses the use of self-organizing maps in a diesel engine management system. Self-organizing maps are one type of artificial neural networks that are good at visualizing data and solving classification problems. The system studied is the Vindax(R) development system from Axeon Ltd. By rewriting the problem formulation also function estimation and conditioning problems can be solved apart from classification problems. </p><p>In this report a feasibility study of the Vindax(R) development system is performed and for implementation the inlet air system is diagnosed and the engine torque is estimated. The results indicate that self-organizing maps can be used in future diagnosis functions as well as virtual sensors when physical models are hard to accomplish.</p>

This master thesis report discusses the use of self-organizing maps in a diesel engine management system. Self-organizing maps are one type of artificial neural networks that are good at visualizing data and solving classification problems. The system studied is the Vindax(R) development system from Axeon Ltd. By rewriting the problem formulation also function estimation and conditioning problems can be solved apart from classification problems. In this report a feasibility study of the Vindax(R) development system is performed and for implementation the inlet air system is diagnosed and the engine torque is estimated. The results indicate that self-organizing maps can be used in future diagnosis functions as well as virtual sensors when physical models are hard to accomplish.

Intelligent fault detection systems using machine learning can be applied to learn to spot anomalies in signals sampled directly from machinery. As a result, expensive repair costs due to mechanical breakdowns and potential harm to humans due to malfunctioning equipment can be prevented. In recent years, Autoencoders have been applied for fault detection in areas such as industrial manufacturing. It has been shown that they are well suited for the purpose as such models can learn to recognize healthy signals that facilitate the detection of anomalies. The content of this thesis is an investigation into the applicability of Autoencoders for fault detection in mobile robotics by assigning anomaly scores to sampled torque signals based on the Autoencoder reconstruction errors and the Mahalanobis distance to a known distribution of healthy errors. An experiment was carried out by training a model with signals recorded from a four-wheeled mobile robot executing a pre-defined diagnostics routine to stress the motors, and datasets of healthy samples along with three different injected faults were created. The model produced overall greater anomaly scores for one of the fault cases in comparison to the healthy data. However, the two other cases did not yield any difference in anomaly scores due to the faults not impacting the pattern of the signals. Additionally, the Autoencoders ability to isolate a fault to a location was studied by examining the reconstruction errors faulty samples determine whether the errors of signals originating from the faulty component could be used for this purpose. Although we could not confirm this based on the results, fault isolation with Autoencoders could still be possible given more representative signals.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-08-28T16:50:59Z No. of bitstreams: 1 WAGNER DE SOUZA PORTO - DISSERTAÇÃO PPGCC 2009..pdf: 3676431 bytes, checksum: 91bede14a64447aa4598ba5c6b3365a4 (MD5) / Made available in DSpace on 2018-08-28T16:50:59Z (GMT). No. of bitstreams: 1 WAGNER DE SOUZA PORTO - DISSERTAÇÃO PPGCC 2009..pdf: 3676431 bytes, checksum: 91bede14a64447aa4598ba5c6b3365a4 (MD5) Previous issue date: 2009-09-16 / Este trabalho apresenta o Auto-FDI (Automatic Fault Detection and Isolation), uma ferramenta de detecção e isolamento de falhas em sistemas. A ferramenta usa o conceito de redundância analítica, onde sinais obtidos do sistema (possivelmente com falha) são comparados com sinais esperados, obtidos de um modelo. O isolamento de falhas emprega uma técnica desenvolvida neste trabalho, chamada isolamento automático. A técnica usa uma abordagem baseada em grafos que considera a propagação de falhas e a falta de informação sobre determinados componentes do sistema. Falhas são localizadas de forma mais precisa possível, dado o nível de detalhe do modelo. No escopo deste trabalho foi abordado todo o processo de especificação, projeto, implementação e validação da ferramenta, utilizada como prova de conceito para a técnica desenvolvida. A validação da ferramenta foi feita através da realização de um estudo de caso por potenciais usuários, o que permitiu demonstrar a aplicabilidade da ferramenta e a da técnica desenvolvida. / This work presents Auto-FDI (Automatic Fault Detection and Isolation), a software tool for detection and diagnosis of faults in systems. The tool uses the analytical redundancy concept, where signals from the (possibly faulty) system are compared with expected signals from a model. The fault isolation employs a technique developed on this work, called automatic isolation. This technique uses a graph-based approach which considers the fault propagation and the lack of information about certain components of the system. Faults are pinpointed as accurately as possible given the level of detail in the model. In the scope of this work was addressed the whole process of specification, design, implementation and validation of the tool - used as proof of concept for the developed technique. The validation of the tool was made by conducting a case study for potential users, that has demonstrated the applicability of the tool and the technique developed.