La fissure d'engrenages peut être considérée comme un défaut des plus compliqués à diagnostiquer car sa signature vibratoire n'est pas vraiment connue. En plus, l'intégration des fissures dans les modèles numériques n'est pas une tâche simple. D'autre part, le diagnostic des engrenages peut être fait dans le domaine temporel à travers des descripteurs statistiques ou dans le domaine fréquentiel grâce à l'analyse spectrale ou l'analyse cepstrale. Lors de l'apparition d'un défaut de fissure, des phénomènes non linéaires et non-stationnaires se manifestent ce qui rend les outils classiques de traitement du signal moins fiables. Dans ce manuscrit, nous répondons à toutes ces problématiques en développant un modèle d'engrenages à 6 DDL qui porte une fissure qui respire. Le modèle nous permet d'étudier la signature de la fissure et son effet sur les vibrations résultantes indépendamment de l'effet des autres composantes du système. Les résultats ont montré que la fissure conduit à une chute de la rigidité d'engrènement. En plus, la respiration de la fissure cause une fatigue dans le matériau ce qui engendre un terme aléatoire dans le signal vibratoire. La combinaison du terme aléatoire avec la composante périodique due à la rotation des arbres conduit à l'apparition de la cyclostationnarité d'ordre 2. Une étude comparative de sensibilité et de robustesse entre la transformée de Fourier rapide, la cyclostationnarité d'ordre 2 et les estimateurs de la phase instantanée (la transformée de Hilbert, estimation of signal parameters via rotational invariance techniques avec une fenêtre glissante, weighted least squares estimation et le scalogramme de phase) est effectuée pour la détection précoce des fissures. En plus, des essais expérimentaux ont été effectués sur un banc d'essais d'engrenages avec différentes dimensions de fissures. Les résultats théoriques et expérimentaux ont montré que l'analyse cyclostationnaire est la méthode la plus sensible et la plus robuste pour la détection précoce des fissures par rapport aux méthodes proposées. De plus, l'analyse de la phase instantanée donne également des résultats intéressants dans le cas des défauts de fissures. Nous avons montré que le scalogramme de phase est, a priori, plus performant que les autres approches / The gear crack is considered as the most complicated failure to diagnose because its vibration signature is not really known. In addition, the integration of crack defect in numerical models is not a simple task. On the other hand, gears diagnosis can be done in the time domain through statistical descriptors or in the frequency domain using spectral analysis or cepstral analysis. During the appearance of a crack defect, nonlinear and nonstationary phenomena occur which makes the classical tools of signal processing unreliable. In this manuscript, we respond to these challenges by developing a gear model of 6 DOF that has a crack that breathes. This allows us to study the signature of the defect in the resulting vibrations with a flexible way away from external vibrations. The results showed that the crack leads to a fall in the mesh stiffness. In addition, the opening and closing of the crack causes a fatigue in the material which generates a random term in the vibration signal. The combination of the random term with periodic component due to the rotation of the shafts leading to the appearance of second-order cyclostationary. A comparative study of sensitivity and robustness between the fast Fourier transform, second-order cyclostationary and estimators of instantaneous phase (the Hilbert transform, Estimation of Signal Parameters via Rotational Invariance Techniques with a sliding window, Weighted Least Squares Estimation and phase scalogramme) is performed for the early detection of cracks. In addition, experimental tests were carried out on a test-bench with different sizes of crack. The theoretical and experimental results showed that the cyclostationary analysis is the most sensitive and most robust method for the early detection of cracks in comparison with the other evaluated methods. Furthermore, the analysis of the instantaneous phase also gives good results in the case of crack defects. We have shown that the phase scalogramme is a priori more efficient than other approaches

High quality noise and vibration measurements outside of a laboratory environment on real life structures and applications are not trivial. True boundary and operating conditions enforce unique challenges on the measurements. Measurements in hazardous situations such as high magnetic fields, and high temperature environments, etc., where ordinary measurement equipment and methods may not be employed, require further precautions. Post measurements objectives such as analysis, design and strategic decisions, e.g., control, rely heavily on the quality and integrity of the measurements (data). The quality of the experimental data is highly correlated with the on-field expertise. Practical or hands-on experience with measurements can be imparted to prospective students, researchers and technicians in the form of laboratory experiments involving real equipment and practical applications. However, achieving expertise in the field of sound and vibration measurements in general and their active control in particular is a time consuming and expensive process. Consequently most institutions can only afford a single setup, resulting in the compromise of the quality of expertise. In this thesis, the challenges in the field of sound and vibration measurements in high magnetic field are addressed. The analysis and measurement of vibration transferred from an operational magnetic resonance imaging (MRI) scanner to adjacent floors is taken as an example. Improvised experimental measurement methods and custom-made frequency analysis techniques are proposed in order to address the challenges and study the vibration transfer. The methods may be extended to other operational industrial machinery and hazardous environments. To encourage and develop expertise in the field of acoustic/vibration measurements and active noise control on practical test beds, remotely controlled laboratory setups are introduced. The developed laboratory setup, which is accessed and controlled via the Internet, is the first of its kind in the active noise control and acoustic measurements area. The laboratory setup can be shared and utilized 24/7 globally, thus reducing the associated costs and eliminating time restrictions.

It is widely acknowledged that bearing failures are the primary reason for breakdowns in rotating machinery. These failures are extremely costly, particularly in terms of lost production. Roller bearings are widely used in industrial machinery and need to be maintained in good condition to ensure the continuing efficiency, effectiveness, and profitability of the production process. The research presented here is an investigation of the use of acoustic emission (AE) to monitor bearing conditions at low speeds. Many machines, particularly large, expensive machines operate at speeds below 100 rpm, and such machines are important to the industry. However, the overwhelming proportion of studies have investigated the use of AE techniques for condition monitoring of higher-speed machines (typically several hundred rpm, or even higher). Few researchers have investigated the application of these techniques to low-speed machines (<100 rpm), This PhD addressed this omission and has established which, of the available, AE techniques are suitable for the detection of incipient faults and measurement of fault growth in low-speed bearings. The first objective of this research program was to assess the applicability of AE techniques to monitor low-speed bearings. It was found that the measured statistical parameters successfully monitored bearing conditions at low speeds (10-100 rpm). The second objective was to identify which commonly used statistical parameters derived from the AE signal (RMS, kurtosis, amplitude and counts) could identify the onset of a fault in either race. It was found that the change in AE amplitude and AE RMS could identify the presence of a small fault seeded into either the inner or the outer races. However, the severe attenuation of the signal from the inner race meant that, while AE amplitude and RMS could readily identify the incipient fault, kurtosis and the AE counts could not. Thus, more attention needs to be given to analysing the signal from the inner race. The third objective was to identify a measure that would assess the degree of severity of the fault. However, once the defect was established, it was found that of the parameters used only AE RMS was sensitive to defect size. The fourth objective was to assess whether the AE signal is able to detect defects located at either the centre or edge of the outer race of a bearing rotating at low speeds. It is found that all the measured AE parameters had higher values when the defect was seeded in the middle of the outer race, possibly due to the shorter path traversed by the signal between source and sensor which gave a lower attenuation than when the defect was on the edge of the outer race. Moreover, AE can detect the defect at both locations, which confirmed the applicability of the AE to monitor the defects at any location on the outer race.

This student thesis aims to analyze the unbalance on rotating machinery by simulation and experimental. The machinery flywheel rotation is modelled as a Single Degree of Freedom (SDOF) and Multi Degree of Freedom (MDOF) system. The model rotation unbalance is simulated by MATLAB. Then the vibration measurement is taken by experimental. In addition, the tachometer is used to determine the flywheel speed calibration. Finally, the rotating unbalance reduction simulation is performed with different parameter value to determine an optimum level of machinery rotation vibration. Unbalance on rotating machinery causes a harmful influence on the environment and machinery. The root cause of rotating unbalance is determined by the simulation and experimental analysis. The analysis result is used as an indicator for predicting machinery breakdown and estimating the correct predictive maintenance action for the machinery. In this project, the simulation and experimental analysis were carried out on a rotating component of the KICKR Snap Bike Trainer. The simulation and numerical analysis are performed by MATLAB programme. On the experimental part, the vibration measurement method and results were discussed. The suggestion of unbalance reduction were recommended base on measurement and vibration analysis results.

Piezoelectric-based energy harvesting devices provide an attractive approach to powering remote devices as ambient mechanical energy from vibrations is converted to electrical energy. These devices have numerous potential applications, including actuation, sensing, structural health monitoring, and vibration control -- the latter of which is of particular interest here. This work seeks to develop an understanding of energy harvesting behavior within the framework of a semi-active technique for reducing turbomachinery blade vibrations, namely resonance frequency detuning. In contrast with the bulk of energy harvesting research, this effort is not focused on maximizing the power output of the system, but rather providing the low power levels required by resonance frequency detuning. The demands of this technique dictate that harvesting conditions will be far from optimal, requiring that many common assumptions in conventional energy harvesting research be relaxed. Resonance frequency detuning has been proposed as a result of recent advances in turbomachinery blade design that have, while improving their overall efficiency, led to significantly reduced damping and thus large vibratory stresses. This technique uses piezoelectric materials to control the stiffness, and thus resonance frequency, of a blade as the excitation frequency sweeps through resonance. By detuning a structure*s resonance frequency from that of the excitation, the overall peak response can be reduced, delaying high cycle fatigue and extending the lifetime of a blade. Additional benefits include reduced weight, drag, and noise levels as reduced vibratory stresses allow for increasingly light blade construction. As resonance frequency detuning is most effective when the stiffness states are well separated, it is necessary to harvested at nominally open- and short-circuit states, corresponding to the largest separation in stiffness states. This presents a problem from a harvesting standpoint however, as open- and short-circuit correspond to zero charge displacement and zero voltage, respectively, and thus there is no energy flow. It is, then, desirable to operate as near these conditions as possible while still harvesting sufficient energy to provide the power for state-switching. In this research a metric is developed to study the relationship between harvested power and structural stiffness, and a key result is that appreciable energy can be harvested far from the usual optimal conditions in a typical energy harvesting approach. Indeed, sufficient energy is available to power the on-blade control while essentially maintaining the desired stiffness states for detuning. Furthermore, it is shown that the optimal switch in the control law for resonance frequency detuning may be triggered by a threshold harvested power, requiring minimal on-blade processing. This is an attractive idea for implementing a vibration control system on-blade, as size limitations encourage removing the need for additional sensing and signal processing hardware.

Identifying faults in machinery before they cause critical failure is the core purpose of condition monitoring. This report gives a background to condition monitoring and outlines the current state of research in the field, and its most important theoretical components. It also describes parallels between sustainability goals and condition monitoring. Further, a method for creating a statistical model to predict faults in machines is described. The proposed model is machine specific and is evaluated on three cases. The model’s predictions is then compared to general limit values provided by an ISO-standard. The model successfully detected faults in time for repair in two of the three cases where the ISO-standard did not. The third case was a control and featured a machine with no issues. Neither our model nor the ISO-standard falsely predicted a fault on the control. From the results of the three cases it is concluded that the proposed machine specific approach is required for reliably predicting faults. / Syftet med tillståndsövervakning är att identifiera fel före de orsakar yterligare fel. Denna rapport ger en bakgrund till tillståndsövervakning samt redogör för den aktuella forskningen och de mest centrala teoretiska grunderna inom området. Rapporten beskriver även hur tillståndsövervakningen bidrar till de globala hållbarhetsmålen samt föreslås en konkret metod för tillämpning av tillståndsövervakning. Den föreslagna modellen är maskinspecifik och grundar sig på statistiska avvikelser av vibrationsdata som samlas från maskiner i ett välfungerande tillstånd. Modellen appliceras på tre olika maskiner och resultaten jämförs med ISO-standarden som har definierat generella gränsvärden för flera maskintyper. Den föreslagna modellen visar lovande resultat genom att upptäcka fel som ISO-standarden missade. Av resultaten från fallen dras slutsatsen att en generella gränsvärden inte är tillräckligt, utan en maskinspecifik metod krävs för att, på ett pålitligt sätt, detektera fel.

The details of an experimental investigation focusing on obtaining the static and vibration characteristics of a full-scale carbon composite wing and fuselage structural assemblies of an ultralight unmanned aerial vehicle (UAV) are presented. The UAV has a total empty weight of 155-lb and an overall length of approximately 20.6t. A three-tier whiffletree system and the tail fixture were designed and used to load the wing and the fuselage in a manner consistent with a high-g flight condition. A shaker-table approach was used for the wing vibration testing, whereas the modal characteristics of the fuselage structure were determined for a freeree configuration. The static responses of the both structures under simulated loading conditions as well as their dynamic properties such as the natural frequency, damping coefficient and associated mode shapes were obtained. The design and implementation of the static and vibration tests along with the experimental results are presented in this thesis.

<p>Vibrating screens are industrial machines used to sort aggregates through their high rotational accelerations. Utilized in mining operations, they are able to screen dozens of tonnes of material per hour. To enhance maintenance and troubleshooting, this thesis introduces a vibration based condition monitoring system capable of observing machine operation. Using acceleration data collected from remote parts of the machine, software continuously detects for abnormal operation triggered by fault conditions. Users are to be notified in the event of a fault and be provided with relevant information.</p> <p>Acceleration data is acquired from a set of sensor devices that are mounted to specified points on the vibrating screen. Data is then wirelessly transmitted to a centralized unit for digital signal processing. Existing sensor devices developed for a previous project have been upgraded and integrated into the monitoring system. Alternative communication technologies and the utilized Wi-Fi network are examined and discussed.</p> <p>The condition monitoring system's hardware and software was designed following engineering principles. Development produced a functional prototype system, implementing the monitoring process. The monitoring technique utilizes signal filtering and processing to compute a set of variables that reveal the status of the machine. Decision making strategies are then employed as to determine when a fault has occurred.</p> <p>Testing performed on the developed monitoring system has also been documented. The performance of the prototype system is examined as different fault scenarios are induced and monitored. Results and descriptions of virtual simulations and live industrial experiments are presented. The relationships between machine faults and detected fault signatures are also discussed.</p> / Master of Applied Science (MASc)

<p>Vibrating screens are mechanical machines used to sort granulated materials based on their particle size. Utilized in the mining industry, these machines can sort tonnes of materials per hour. In the past, McMaster University developed sensor devices that measure and transmit vibration data of these machines to a central data acquisition unit for analysis, tuning, and maintenance purposes. In this thesis, I present the development of two new software systems that are used to process, manage, and present the information gained from these measurements. The first system, the offline vibration analysis software, is used to analyze the vibration data in both time and frequency domain, and presents the measured and calculated data in textual and graphical forms. The second system, the online vibration analysis software, is used by vibrating screens manufacturers and their customers to gather and manage vibration data collected from their vibrating screens by utilizing a central storage. The development process of these systems followed an iterative and incremental approach with continuous feedback from stakeholders. It included extensive requirements gathering to define a model, in terms of data representation, that captures the business logic and practices of the industry. Furthermore, it used standard architectures such as Model View Controller (MVC) and advanced technologies such as Object Relationship Mapping (ORM) for data access to increase flexibility and maintainability. Finally, comprehensive unit testing and thorough security risks evaluation were conducted in order to ensure that these systems are secure and bug free.</p> / Master of Applied Science (MASc)

The precise and detailed characterization of the dynamic response of structures has become increasingly important in recent years. As a consequence, the accuracy of experimental data, which is often used to validate and update finite element models, has become extremely important. However, as researchers have attempted to identify and quantify sources of error in the experimental modal analysis (EMA) process, an important potential error source has been largely overlooked. Instabilities in the dynamic response of structures due to small variations in test environmental conditions may result in significant errors in experimental and analytical results, leading to erroneous and/or misleading conclusions. This thesis presents an experimental and analytical investigation of the effects of ambient temperature variations on the dynamic characteristics of a thin, square steel plate. The modal properties of the plate with two different boundary conditions and at temperatures above and below standard room temperature are examined. In addition, an analytical model is developed accounting for the effects of temperature-dependent material properties. Results indicate that natural frequencies and damping are significantly affected by changes in temperature. In the case of the natural frequency variations, the temperature-dependence of Young's modulus is the dominant factor, but boundary condition effects may also be important. Also, FRF magnitudes at spectral lines close to the resonances are very sensitive to temperature. Finally, only minor variations in the plate response shapes are observed, although significant changes in the imaginary component of the velocity field are evident. / Master of Science