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The sideband phenomenon is a common but obscure characteristic of the Rotary Dynamics field. In the automotive industry these sidebands have been found to produce a poor sound quality, resulting in customer dissatisfaction and warranty returns. In the interest of continued product improvement, research and development must resolve uncertainties in the current design methods. Qualitative relationships between the sideband characteristics and design parameters have developed in recent years, but the quantitative goal hasn't been achieved. A Synchronous Sampling (SS) data acquisition system is applied to a helical planetary gear set to improve the understanding of the sideband characteristics and enhance the design process. An optical encoder, a component of the SS system, mechanically locked to the rotating system controls the A/D converter to sample at constant shaft angle increments. The phase-locked nature of SS allows the use of vector averaging to significantly lower the noise floor and improve the representation of the order domain. In this work, the advantages of using a SS system with vector averaging capabilities are compared to the disadvantages of using a fixed sampling (FS) system. Utilizing the SS tool, this work also illustrates the influences of loading styles and values and speed on a gearmesh and its dominant sideband orders. Inspection of these influences suggests an opportunity for future work. / Master of Science

This thesis reports on the setup of a new ion trap apparatus designed for experiments with single ⁴⁰Ca⁺ ions to perform molecular spectroscopy. The calcium ion is laser cooled, allowing for sympathetic cooling of the nonfluorescing molecular ion. The aim of these experiments is to explore loading and identifying molecular ions in RF-Paul traps, as well as developing new spectroscopic tools to measure transitions of molecular ions via the fluorescence of co-trapped ⁴⁰Ca⁺ ions. Ground state cooling of a mixed ion pair is implemented as a first step towards increasing the sensitivity of our technique to the level necessary to measure transitions with low scattering rates (like those present in molecular ions). Doppler cooling on the S(1/2)->P(1/2) transition of the calcium ion results in the formation of a Coulomb crystal, the behavior of which may be used to infer properties of the molecular ion. Following cooling, sideband spectroscopy on the narrow S(1/2)->D(5/2) quadrupole transition of calcium may be used to identify the mass of single molecular ions. This method is verified via a non-destructive measurement on ⁴⁰CaH⁺ and ⁴⁰Ca¹⁶O⁺. The normal modes of the Coulomb crystal can also be used to extract information from the target ion to the control ion. By driving the blue side of a transition, laser induced heating can be put into the two ion system, which leads to changes in fluorescence of the ⁴⁰Ca⁺ ion, first demonstrated with two Ca⁺ isotopes. Increasing the sensitivity of this technique requires ground state cooling of both the ⁴⁰Ca⁺ ion and the ion of interest, enabling the transfer of the ion's motional state into the ground state with high probability. This thesis demonstrates ground state cooling of the atomic ion and sympathetic cooling of a second ion (⁴⁴Ca⁺). Once in the ground state, heating of the Coulomb crystal by scattering photons off of the spectroscopy ion can be measured by monitoring the resolved motional sidebands of the S(1/2)->D(5/2) transition of ⁴⁰Ca⁺, allowing for spectral lines to be inferred. Future experiments will investigate this technique with molecular ions.

La surveillance automatique consiste à vérifier le bon fonctionnement d'un système tout au long de sa durée d'utilisation et ce, sans intervention humaine. Elle permet de mettre en place une stratégie de maintenance prévisionnelle qui présente un intérêt économique majeur, en particulier dans le cas de systèmes isolés comme les éoliennes construites en pleine mer. La surveillance automatique se base sur l'acquisition plus ou moins régulière de signaux pendant le fonctionnement du système surveillé. L'analyse de ces signaux doit permettre d'établir un diagnostic et de prendre une décision sur le déclenchement des opérations de maintenance. Dans cette thèse, nous proposons une méthode d'analyse générique permettant de s'adapter à n'importe quel système surveillé. La méthode se déroule en plusieurs étapes. Premièrement, chaque signal est analysé individuellement pour en extraire son contenu spectral, c'est-à-dire identifier les pics spectraux, les séries harmoniques et les bandes de modulation présents dans sa densité spectrale. Ensuite, ce contenu spectral est suivi au cours du temps pour former des trajectoires sur l'ensemble de la séquence de signaux acquis. Ces trajectoires permettent de générer des tendances qui sont le reflet de la santé du système. Enfin, les tendances sont analysées pour identifier un changement au cœur du système qui serait synonyme d'usure ou de défaut naissant. Cette méthodologie est validée sur de nombreux signaux réels provenant de la surveillance de différents systèmes mécaniques. / The automatic monitoring consists in verifying without any human intervention that a system is operating well. The monitoring allows to use a predictive maintenance strategy, which is economically interesting, especially in the case of isolated systems like off-shore wind turbines. The automatic monitoring is based on signals acquired more or less regularly while the monitored system is operating. The analysis of these signals should be sufficient to diagnose the system and to decide whether or not the maintenance operations should be done. In this thesis, we propose a generic analysis method able to adapt itself to any monitored system. This method is composed by several steps. First, each signal is analyzed individually in order to extract its spectral content, that is to identify the spectral peaks, the harmonic series and the modulation sidebands presents in the signal spectrum. Then, the spectral content is tracked through time to construct spectral trajectories in the sequence of acquired signal. These trajectories are used to generate trends which indicate the state of the system health. Finally, the trends are analyzed to identify a change in the system response which would indicate some wear or a fault in is early stage. This analysis method is validated on real world signals acquired on different mechanical systems.

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