Global ETD Search

61	Condition Monitoring : Using Computational intelligence methods Kotta, Anwesh 06 November 2015 (has links) (PDF) Machine tool components are widely used in many industrial applications. In accordance with their usage, a reliable health monitoring system is necessary to detect defects in these components in order monitor machinery performance and avoid malfunction. Even though several techniques have been reported for fault detection and diagnosis, it is a challenging task to implement a condition monitoring system in real world applications due to their complexity in structure and noisy operating environment. The primary objective of this thesis is to develop novel intelligent algorithms for a reliable fault diagnosis of machine tool components. Another objective is to use Micro Electro Mechanical System (MEMS) sensor and interface it with Raspberry pi hardware for the real time condition monitoring. Primarily knowledge based approach with morphological operators and Fuzzy Inference System is proposed, the e˙ectiveness of this approach lies in the selection of structuring elements(SEs). When this is evaluated with di˙erent classes of bearing fault signals, it is able to detect the fault frequencies e˙ectively. Secondarily, An analytical approach with multi class support machine is proposed, this method has uniqueness of learning on its own with out any prior knowledge, the e˙ectiveness of this method lies on selected features and used kernel for converging. Results have shown that RBF (Radial Bias Function) kernel, which is commonly known as gauss kernel has good performance in identifying faults with less computation time. An idea of prototyping these methods has triggered in using Micro Electro Mechanical System (MEMS) sensor for data acquisition and real time Condition Monitoring. LIS3DH accelerometer sensor is used for the data acquisition of spindle for capturing high frequency fault signals. The measured data is analyzed and compared with the industrial sensor k-shear accelerometer type 8792A. Zustandsüberwachung Fuzzy-Theorie Support Vektor Maschinen Condition Monitoring fuzzy theory support vector maschine ddc:004 Zustandsüberwachung
62	Multivariate Analyse instationärer Zeitreihen Integration und Kointegration in Theorie und Simulation / Stroe-Kunold, Esther. January 2006 (has links) Heidelberg, Univ., Dipl.-Arb., 2005.
63	Digitale Wasserzeichen für geographische 2D-Vektordaten Voigt, Michael January 2006 (has links) Zugl.: Darmstadt, Techn. Univ., Diss., 2006
64	Swiss monetary policy rules, effects, and indicators Perruchoud, Alexander January 2007 (has links) Zugl.: Basel, Univ., Diss., 2007 / Erscheinungsjahr auf der Haupttitels.: 2007
65	Polen auf dem Weg zur Wirtschafts- und Währungsunion der flexible Wechselkurs als ein Instrument zur Absorption asymmetrischer Schocks Sta̜żka, Agnieszka January 2007 (has links) Zugl.: Freiburg (Breisgau), Univ., Diss., 2007
66	Einsatzpotential von support vector machines (SVM)-Klassifikation für Scoring-Fragestellungen im Database-Marketing empirische Untersuchung am Beispiel der Kündigungsprognose von Zeitschriftenabonnements Zimmermann, Martin January 2008 (has links) Zugl.: Jena, Univ., Diss., 2008
67	Ixodes ricinus (Ixodidae) saisonale Aktivität und natürliche Infektionen mit dem FSME-Virus an ausgewählten Standorten in Bayern Kupča, Anne Martina January 2009 (has links) Zugl.: München, Univ., Diss., 2009
68	Multivariate panel models : some new results and their application to the analysis of economic growth / Bröck, Susanne. Unknown Date (has links) Frankfurt (Main), University, Diss., 2008.
69	Polen auf dem Weg zur Wirtschafts- und Währungsunion : Der flexible Wechselkurs als ein Instrument zur Absorption asymmetrischer Schocks Stążka, Agnieszka January 2008 (has links) Zugl.: Freiburg <Breisgau>, Univ., Diss., 2007.
70	Untersuchungen zum Zeckenbefall und zur Prävalenz von Borrelia burgdorferi sowie Babesia divergens beim Rind im bayerischen Voralpenland Lengauer, Heidi. Unknown Date (has links) (PDF) Universiẗat, Diss., 2004--München.

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