Conventional rotating machine vibration monitoring techniques are based on the assumption that changes in the measured structural response are caused by deterioration in the condition of the rotating machine. However, due to variations of the rotational speed, the measured signal may be non-stationary and difficult to interpret. For this reason, the order tracking technique is introduced. One of main advantages of order tracking over traditional vibration monitoring lies in its ability to clearly identify non-stationary vibration data and to a large extent exclude the influences of varying rotational speed. In recent years, different order tracking techniques have been developed. Each of these has their own pros and cons in analyzing rotating machinery vibration signals. In this research, three existing order tracking techniques are extensively investigated and combined to further explore their abilities in the context of condition monitoring. Firstly, computed order tracking is examined. This allows non-stationary effects due to the variation of rotational speed to be largely excluded. However, this technique was developed to deal with the entire raw signal and therefore looses the ability to focus on each individual order of interest. Secondly, Vold-Kalman filter order tracking is considered. It is widely reported that this technique overcomes many of the limitations of other order tracking methods and extracts order signals into the time domain. However because of the adaptive nature of the Vold-Kalman filter, the non-stationary effects due to the rotational speed will remain in the extracted order waveform, which is not ideal for conventional signal processing methods such as Fourier analysis. Yet, the strict mathematical filter (the Vold-Kalman filter is based upon two rigorous mathematical equations, namely the data equation and the structural equation, to realize the filter) gives this technique an excellent ability to focus on the orders of interest. Thirdly, the empirical mode decomposition method is studied. In the literature, this technique is claimed to be an effective diagnostic tool for various kinds of applications including diagnosis of rotating machinery faults. Its unique empirical way of extracting non-stationary and non-linear signals allows it to capture machine fault information which is intractable by other order tracking methods. But since there is no precise mathematical definition for an intrinsic mode function in empirical mode decomposition and – as far as could be ascertained – no published assessment of the relationship between an order and an intrinsic mode function, this technique has not been properly considered by analysts in terms of order tracking. As a result, its abilities have not really been explored in the context of order related vibrations in rotating machinery. In this research, the relationship between an order and an intrinsic mode function is discussed and it is treated as a special kind of order tracking method. In stead of focusing individually on each order tracking technique, the current work synthesizes different order tracking techniques. Through combination, exchange and reconciliation of ideas between these order tracking techniques, three improved order tracking techniques are developed for the purpose of enhancing order tracking analysis in condition monitoring. The techniques are Vold-Kalman filter and computed order tracking (VKC-OT), intrinsic mode function and Vold-Kalman filter order tracking (IVK-OT) and intrinsic cycle re-sampling (ICR). Indeed, these improved approaches contribute to current order tracking practice, by providing new order tracking methods with new capabilities for condition monitoring of systems which are intractable by traditional order tracking methods, or which enhances results obtained by these traditional methods. The work commences with a discussion of the inter-relationship between the order tracking methods which are considered in the thesis, and exposition of the scope of the work and an explanation of the way these independent order tracking techniques are integrated in the thesis. To demonstrate the abilities of the improved order tracking techniques, two simulation models are established. One is a simple single-degree-of-freedom (SDOF) rotor model with which VKC-OT and IVK-OT techniques are demonstrated. The other is a simplified gear mesh model through which the effectiveness of the ICR technique is proved. Finally two experimental set-ups in the Sasol Laboratory for Structural Mechanics at the University of Pretoria are used for demonstrating the improved approaches for real rotating machine signals. One test rig was established to monitor an automotive alternator driven by a variable speed motor. A stator winding inter-turn short was artificially introduced. Advantages of the VKC-OT technique are presented and features clear and clean order components under non-stationary conditions. The diagnostic ability of the IVK-OT technique of further decomposing an intrinsic mode function is also demonstrated via signals from this test rig, so that order signals and vibrations that modulate orders in IMFs can be separated and used for condition monitoring purposes. The second experimental test rig is a transmission gearbox. Artificially damaged gear teeth were introduced. The ICR technique provides a practical alternative tool for fault diagnosis. It proves to be effective in diagnosing damaged gear teeth. / Thesis (PhD)--University of Pretoria, 2011. / Mechanical and Aeronautical Engineering / unrestricted

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Machine health and condition monitoring are billion-dollar concerns for industry. Quality control and continuous improvement are some of the most important factors for manufacturers to consider in order to maintain a successful business. When work floor interruptions occur, engineers frequently employ “Band-Aid” fixes due to resource, timing, or technical constraints without solving for the root cause. Thus, a need for quick, reliable, and accurate fault detection and diagnosis methods are required. Within complex rotating machinery, a fundamental component that accounts for large amounts of downtime and failure involves a very basic yet crucial element, the rolling-element bearing. A worn-out bearing constitutes to some of the most drastic failures in any mechanical system next to electrical failures associated with stator windings. The cyclical motion provides a way for measurements to be taken via vibration sensors and analyzed through signal processing techniques. Methods will be discussed to transform these acquired signals into usable input data for neural network training in order to classify the type of fault that is present within the system. With the wide-spread utilization and adoption of neural networks, we turn our attention to the growing field of sequence-to-sequence deep learning architectures. Language based models have since been adapted to a multitude of tasks outside of text translation and word prediction. We now see powerful Transformers being used to accomplish generative modeling, computer vision, and anomaly detection -- spanning across all industries. This research aims to determine the efficacy of the Transformer neural network for use in the detection and classification of faults within 3-phase induction motors for the automotive industry. We require a quick turnaround, often leading to small datasets in which methods such as data augmentation will be employed to improve the training process of our time-series signals. / Thesis / Master of Applied Science (MASc)

Récemment, le diagnostic des machines tournantes devient un des sujets de recherche les plus importants. Plusieurs axes sont développés dans ce domaine : traitement de signal, reconnaissance des formes et autres. En plus, les systèmes industriels peuvent être surveillés à distance en temps réel grâce à la disponibilité de l’internet. Cette surveillance se trouve exigeante au niveau de l’acquisition et le stockage des données. En 2004, le Compressive Sensing est introduit dans le but d’acquérir les données a une basse fréquence afin d’économiser l’énergie dans les réseaux de capteurs sans fils. Des résultats similaires peuvent être achevés par l’Echantillonnage Aléatoire qui procure une acquisition à basse fréquence grâce à sa propriété d’anti-repliement. Comme cette technique d’échantillonnage est jusqu’à l’instant de la rédaction de cette thèse n’est pas encore disponible au marché, le travail sur ce sujet se trouve promettant afin de présenter une implémentation pratique validée. D’où, la contribution de cette thèse est de présenter les différentes propriétés de l’échantillonnage aléatoire à travers une étude théorique détaillée dans le domaine temporel et fréquentiel suivie d’une simulation et d’une application pratique sur des signaux synthétisés simples puis sur des signaux de vibration extraits des principaux composants des machines : roulements et engrenages. Les résultats obtenus au niveau de la simulation et la pratique sont satisfaisants grâce à la diminution de la fréquence d’échantillonnage et la quantité de données à sauvegarder ce qui peut être considéré comme une résolution de la problématique de la surveillance à temps réel / Nowadays, machine monitoring and supervision became one of the most important domains of research. Many axes of exploration are involved in this domain: signal processing, machine learning and several others. Besides, industrial systems can now be remotely monitored because of the internet availability. In fact, as many other systems, machines can now be connected to any network by a specified address due to the Internet of Things (IOT) concept. However, this combination is challenging in data acquisition and storage. In 2004, the compressive sensing was introduced to provide data with low rate in order to save energy consumption within wireless sensor networks. This aspect can also be achieved using random sampling (RS). This approach is found to be advantageous in acquiring data randomly with low frequency (much lower than Nyquist rate) while guaranteeing an aliasing-free spectrum. However, this method of sampling is still not available by hardware means in markets. Thus, a comprehensive review on its concept, its impact on sampled signal and its implementation in hardware is conducted. In this thesis, a study of RS and its different modes is presented with their conditions and limitations in time domain. A detailed examination of the RS’s spectral analysis is then explained. From there, the RS features are concluded. Also, recommendations regarding the choice of the adequate mode with the convenient parameters are proposed. In addition, some spectral analysis techniques are proposed for RS signals in order to provide an enhanced spectral representation. In order to validate the properties of such sampling, simulations and practical studies are shown. The research is then concluded with an application on vibration signals acquired from bearing and gear. The obtained results are satisfying, which proves that RS is quite promising and can be taken as a solution for reducing sampling frequencies and decreasing the amount of stored data. As a conclusion, the RS is an advantageous sampling process due to its anti-aliasing property. Further studies can be done in the scope of reducing its added noise that was proven to be cyclostationary of order 1 or 2 according to the chosen parameters

Cette thèse propose trois méthodes de traitement du signal orientées vers la surveillance d’état et le diagnostic. Les techniques proposées sont surtout adaptées pour la surveillance d’état, effectuée à la base de vibrations, des machines tournantes qui fonctionnent dans des conditions d’opération non-stationnaires comme par exemple les éoliennes mais elles ne sont pas limitées à un tel usage. Toutes les méthodes proposées sont des algorithmes automatiques et gérés par les données.La première technique proposée permet de sélectionner la partie la plus stationnaire d’un signal en cadrant la représentation temps-fréquence d’un signal.La deuxième méthode est un algorithme pour l’association des dispositions spectrales, des séries harmoniques et des séries à bandes latérales avec des fréquences caractéristiques provennant du cinématique d'un système analysé. Cette méthode propose une approche unique dédiée à l’élément roulant du roulement qui permet de surmonter les difficultés causées par le phénomène de glissement.La troisième technique est un algorithme de démodulation de bande latérale entière. Elle fonctionne à la base d’un filtre multiple et propose des indicateurs de santé pour faciliter une évaluation d'état du système sous l’analyse.Dans cette thèse, les méthodes proposées sont validées sur les signaux simulés et réels. Les résultats présentés montrent une bonne performance de toutes les méthodes. / This thesis proposes a three signal-processing methods oriented towards the condition monitoring and diagnosis. In particular the proposed techniques are suited for vibration-based condition monitoring of rotating machinery which works under highly non-stationary operational condition as wind turbines, but it is not limited to such a usage. All the proposed methods are automatic and data-driven algorithms.The first proposed technique enables a selection of the most stationary part of signal by cropping time-frequency representation of the signal.The second method is an algorithm for association of spectral patterns, harmonics and sidebands series, with characteristic frequencies arising from kinematic of a system under inspection. This method features in a unique approach dedicated for rolling-element bearing which enables to overcome difficulties caused by a slippage phenomenon.The third technique is an all-sideband demodulation algorithm. It features in a multi-rate filter and proposes health indicators to facilitate an evaluation of the condition of the investigated system.In this thesis the proposed methods are validated on both, simulated and real-world signals. The presented results show good performance of all the methods.

Made available in DSpace on 2014-06-11T19:27:13Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-05-26Bitstream added on 2014-06-13T19:55:33Z : No. of bitstreams: 1 galavotti_tv_me_ilha.pdf: 4073080 bytes, checksum: 0605ef5edb68c7bc2b71f8c976c0fe09 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Nos últimos anos, as indústrias têm mostrado bastante interesse no desenvolvimento de novas técnicas para o controle de vibrações. O objetivo principal é atribuir valores aceitáveis das amplitudes de vibrações nos sistemas, garantindo um bom funcionamento dos mesmos e evitando falhas que provoquem paradas abruptas, mostrando-se uma área científica muito importante e que aproxima vários campos da engenharia moderna. Atualmente essa tecnologia é crescente e grande investimento tem sido aplicado no seu desenvolvimento. Este trabalho apresenta resultados obtidos para técnicas ativas e semi-ativas de controle de vibrações, considerando que as modificações estruturais são provenientes da alteração da rigidez e amortecimento. Utiliza-se para essa análise, Amortecedores Ativos Controlados por Atuadores Piezelétricos, denominados em inglês por Piezoelectric Friction Damper (PFD). A aplicação da metodologia é realizada em máquinas rotativas modeladas pelo Método dos Elementos Finitos e em um protótipo projetado e construído em laboratório. Os resultados procuram atenuar os níveis de vibrações e demonstram a viabilidade da aplicação de PFDs em estruturas. / Nowadays industries have shown great interest in developing new techniques for vibration control. The target is getting acceptable values of the amplitudes of vibrations in systems, ensuring proper working order avoiding failures. This is a scientific area of very important and approach fields of modern engineering. Currently this technology is growing and large investments has been applied in its development. This paper presents results obtained for active and semi-active techniques vibration control, where the structural changes are from the modification of stiffness and damping. It is used for this analysis a system known by Piezoelectric Friction Damper (PFD). The methodology was applied in rotating machines modeled by finite element method and in a prototype designed and built in the laboratory. The results try to mitigate the vibration levels and demonstrate the feasibility of applying PFDs in rotating machine.

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Denna rapport är ett resultat av utförd fallstudie på Siemens Industrial Turbomachinery AB. Studien utfördes som ett DMAIC-projekt i syfte att utvärdera befintlig processtyrning och ge förslag på nya styrparametrar för att styra och övervaka tillverkningsprocessen av rotorer. En rotor skapas genom montage av turbinmodul på kompressorrotor. För att säkerställa rotorns funktionalitet mäts rotorkast kontinuerligt under tillverkningprocessen. Stora rotorkast uppstår sporadiskt vid montaget varpå nuvarande avhjälpningsmetod  innefattar tids- och kostnadskrävande demontage och återmontage av turbinmodul på kompressorrotor.  Rekommendationer har utformats och baserats utifrån historiskt analyserad data, insamlad mellan åren 2013 och 2020, 19 intervjuer och 2 workshops. Rekommendationer innefattar implementering av statistisk processtyrning. Ett av argumenten till implementeringen är att börja utvärdera effekten av genomförda förbättringsprojekt. Denna studie identifierade ett förbättringsprojekt, genomfört år 2016, som ökade andelen defekter med 454%. Då förbättringsprojektet tros bidragit med en förbättring i ett annat processteg ges rekommendationen att utvärdera helheten av implementerad förbättringsåtgärd. Avslutningsvis rekommenderas att uppdatera dagens bristfälliga processtyrning genom beräknandet av nya toleranser baserat på önskad kvalitetsnivå och eliminera diskrepanserna mellan de idag använda toleranserna. / This report is a result of a case study carried out at Siemens Industrial Turbomachinery AB. The study was conducted as a DMAIC project with the aim of evaluating existing process control and proposing new control parameters for controlling and monitoring the manufacturing pro- cess of rotors. A rotor is created by the assembly of a turbine module on a compressor rotor. In order to ensure the functionality of the rotor, rotor-runout is continuously measured during the manufacturing process. Large rotor-runouts occur sporadically during assembly and the current method to fix the abnormalities includes time- and costly disassembly and re-assembly of the turbine module on the compressor rotor. Recommendations have been designed after analysis of historical data collected between 2013 and 2020, 19 interviews and 2 workshops. Recom- mendations include implementation of statistical process control. One of the arguments for the implementation is to start evaluating the effects of completed improvement projects. This study identified an improvement project, completed in 2016, which increased the proportion of defects by 454%. Since the improvement project is believed to have contributed to an enhancement in another part of the process, a more holistic way of evaluation is needed to follow up effects of improvements projects. Finally, it is recommended to update the tolerances by calculating new ones based on the desired quality level while also eliminating the discrepancies between the different tolerances used today.