With the advancement of automated control systems in the past few years, the focus has also been moved to safer, more reliable systems with less harmful effects on the environment. With increased job mobility, less experienced operators could cause more damage by incorrect identification and handling of plant faults, often causing faults to progress to failures. The development of an automated fault detection and diagnostic system can reduce the number of failures by assisting the operator in making correct decisions. By providing information such as fault type, fault severity, fault location and cause of the fault, it is possible to do scheduled maintenance of small faults rather than unscheduled maintenance of large faults. Different fault detection and diagnostic systems have been researched and the best system chosen for implementation as a distributed fault detection and diagnostic architecture. The aim of the research is to develop a distributed fault detection and diagnostic system. Smaller building blocks are used instead of a single system that attempts to detect and diagnose all the faults in the plant. The phases that the research follows includes an in-depth literature study followed by the creation of a simplified fault detection and diagnostic system. When all the aspects concerning the simple model are identified and addressed, an advanced fault detection and diagnostic system is created followed by an implementation of the fault detection and diagnostic system on a physical system. / Thesis (M.Ing. (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2009.

With the advancement of automated control systems in the past few years, the focus has also been moved to safer, more reliable systems with less harmful effects on the environment. With increased job mobility, less experienced operators could cause more damage by incorrect identification and handling of plant faults, often causing faults to progress to failures. The development of an automated fault detection and diagnostic system can reduce the number of failures by assisting the operator in making correct decisions. By providing information such as fault type, fault severity, fault location and cause of the fault, it is possible to do scheduled maintenance of small faults rather than unscheduled maintenance of large faults. Different fault detection and diagnostic systems have been researched and the best system chosen for implementation as a distributed fault detection and diagnostic architecture. The aim of the research is to develop a distributed fault detection and diagnostic system. Smaller building blocks are used instead of a single system that attempts to detect and diagnose all the faults in the plant. The phases that the research follows includes an in-depth literature study followed by the creation of a simplified fault detection and diagnostic system. When all the aspects concerning the simple model are identified and addressed, an advanced fault detection and diagnostic system is created followed by an implementation of the fault detection and diagnostic system on a physical system. / Thesis (M.Ing. (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2009.

Yes / Diagnostics and prognostics have significant roles in the reliability enhancement of systems and are focused topics of active research. Engineered systems are becoming more complex and are subjected to miscellaneous failure modes that impact adversely their performability. This everincreasing complexity makes fault diagnostics and prognostics challenging for the system-level functions. A significant number of successes have been achieved and acknowledged in some review papers; however, these reviews rarely focused on the application of complex engineered systems nor provided a systematic review of diverse techniques and approaches to address the related challenges. To bridge the gap, this paper firstly presents a review to systematically cover the general concepts and recent development of various diagnostics and prognostics approaches, along with their strengths and shortcomings for the application of diverse engineered systems. Afterward, given the characteristics of complex systems, the applicability of different techniques and methods that are capable to address the features of complex systems are reviewed and discussed, and some of the recent achievements in the literature are introduced. Finally, the unaddressed challenges are discussed by taking into account the characteristics of automotive systems as an example of complex systems. In addition, future development and potential research trends are offered to address those challenges. Consequently, this review provides a systematic view of the state of the art and case studies with a reference value for scholars and practitioners.

Yes / This paper provides a critical review and discussion of major challenges with automotive aftertreatment systems from the viewpoint of the reliability of complex systems. The aim of this review is to systematically explore research efforts towards the three key issues affecting the reliability of aftertreatment systems: physical problems, control problems and fault diagnostics issues. The review covers important developments in technologies for control of the system, various methods proposed to tackle NOx sensor cross-sensitivity as well as fault detection and diagnostics methods, utilized on SCR, LNT and DPF systems. This paper discusses future challenges and research direction towards assured dependability of complex cyber-physical systems. / InPowerCare Project - JLR (Jaguar Land Rover)

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This dissertation proposes several simple, robust, and non-intrusive condition monitoring methods for induction motors fed by closed-loop inverters and claw-pole generators with built-in rectifiers. While the flexible energy forms synthesized by power electronic converters greatly enhance the performance and expand the operating region of induction motors and claw-pole generators, they also significantly alter the fault behavior of these electric machines and complicate the fault detection and protection. In this dissertation, special characteristics of the connected closed-loop inverter and rectifier have been thoroughly analyzed, with particular interest in their impact on fault behaviors of the induction motor and the claw-pole generator. Based on the findings obtained from the theoretical and experimental analysis, several sensorless thermal, mechanical, and insulation monitoring methods are proposed by smartly utilizing special features and capabilities of the connected power electronic converter. A simple and sensitive stator turn-fault detector is proposed for induction motors fed by closed-loop inverter. In addition, a stator thermal monitoring method based on active DC current injection and direct voltage estimation is also proposed to prevent the closed-loop controlled induction motors from thermally overloading. The performance of both methods is demonstrated by extensive experimental results. Methods to detect serpentine belt slip, serpentine belt defect, rotor eccentricity have been proposed for claw-pole generators using only the available electric sensor information. Methods to detect and protect stator turn faults in claw-pole generators are also presented in this dissertation. Lastly, a novel method to detect the generalized bearing roughness fault is proposed. All the proposed condition monitoring techniques have been validated by experimental results.

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.

Submitted by RODOLFO DE SOUSA SANTOS null (rodolfosousa4@gmail.com) on 2017-08-24T18:31:09Z No. of bitstreams: 1 TESE _RODOLFO_CORRIGIDA_19_08_2017_Final.pdf: 4285264 bytes, checksum: b5dac391b40121a31b55502fba5c1c43 (MD5) / Approved for entry into archive by Luiz Galeffi (luizgaleffi@gmail.com) on 2017-08-25T16:18:27Z (GMT) No. of bitstreams: 1 santos_rs_dr_guara.pdf: 4285264 bytes, checksum: b5dac391b40121a31b55502fba5c1c43 (MD5) / Made available in DSpace on 2017-08-25T16:18:27Z (GMT). No. of bitstreams: 1 santos_rs_dr_guara.pdf: 4285264 bytes, checksum: b5dac391b40121a31b55502fba5c1c43 (MD5) Previous issue date: 2017-07-21 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Os sinais de vibrações de máquinas rotativas conduzem a informações dinâmicas da máquina e esta análise é de grande importância no que diz respeito ao monitoramento de condição e diagnósticos de máquinas. Vários métodos de análises têm sido empregados no sentido de diagnosticar falhas em componentes de máquinas tais como engrenagens, rolamentos, dentre outros. Este trabalho apresenta uma análise sobre detecção de falhas em rolamentos de máquinas rotativas, e para esta apreciação utilizou-se os bancos de dados da CASE WESTERN RESERV UNIVERSITY e o banco de dados da FEG/UNESP. O objetivo principal deste trabalho foi a implementação de técnicas avançadas para identificar e caracterizar as falhas que são geradas em rolamentos, vislumbrando o aprimoramento da manutenção baseada na condição. Inicialmente, realizou-se a implementação e simulação no banco de dados da (CWRU), utilizando o software MATLAB e por meio da técnica de ressonância de alta frequência (HFRT), obteve-se resultados satisfatórios, entretanto esta metodologia é limitada uma vez que ela é empregada apenas para regime estacionário. A implementação da técnica HFRT não identificou em alguns casos a frequências para caracterização dos defeitos nas pistas dos rolamentos. Em seguida, utilizou-se a técnica Short Time Fourier Transform-STFT. A implementação proporcionou uma análise bem mais sensível aos impactos gerados nas pistas, pois, com a utilização da STFT, foi possível identificar as frequências características de defeitos. Para efeito de comparação optou-se por utilizar a técnica Wavelet combinada com a técnica do envelope. Esta análise foi aplicada usando a Wavelet Daubechies de ordem 4 (db4), em cuja implementação, realizou-se a decomposição do sinal de um rolamento com defeito e verificou-se qual destes apresentou o maior nível RMS e selecionou-se este sinal, pois o mesmo é o nível ideal para aplicação do método. Realizou-se a mesma apreciação ao banco de dados da FEG/UNESP. A análise realizada da técnica de Wavelet combinada com a técnica HFRT foi a que demonstrou melhor capacidade em relação às técnicas HFRT e STFT. Em seguida realizou-se a implementação da técnica de curtose espectral associada à técnica do envelope foi a que proporcionou os resultados mais precisos e satisfatórios, pois com a aplicação dessa metodologia foi possível a determinação de forma automática da região de ressonância e consequentemente uma melhora na caracterização das frequências de defeitos observadas nos rolamentos dos experimentos realizados em máquinas rotativas. / The vibration signals from rotating machines provide a set of dynamic information, which are very important for continuous condition monitoring of machinery. Several analytical methods have been employed in order to diagnose faults in machines components such as gears, bearings and others. This paper presents a fault detection analysis of rotating machinery bearings, using data from CASE WESTERN UNIVERSITY RESERVOIR and the FEG / UNESP database. The main objective of this work is the implementation of advanced techniques to identify and characterize bearing failures, with the purpose to improve maintenance under working conditions. At first, the implementation and simulation were done with data extracted from the database of (CWRU) using MATLAB software and high-frequency resonance technique (HFRT), which led to satisfactory results. However, this technique is limited since it is used only in a stationary regime. In some cases, the implementation of HFRT technique was not able to identify the defect frequencies of the bearing’s races. Next the STFT Short-Time Fourier Transform technique was used. Its implementation provided a much more sensitive analysis of the impacts on the slopes; using STFT allowed to identify the characteristic defect frequencies. For comparison purposes, the wavelet technique combined with the envelope technique were used. This analysis was applied using Daubechies Wavelet of order 4 (DB4). In its implementation, a defective bearing signal was decomposed into various parts. The signal part with the highest RMS level was selected, because it provides best conditions for applying the method. Analogously, data from the FEG / UNESP database were treated. The Wavelet analysis technique combined with HFRT technique demonstrated better capability with respect to the HFRT and STFT techniques. The implementation of the spectral kurtosis technique associated with the envelope technique provided the most accurate and satisfactory results, since with the application of this methodology it was possible to determine the resonance region automatically. Consequently, this is an improvement regarding the characterization of the defect frequencies of the bearings observed in experiments with rotating machinery.

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