Vibration-Based Fault-Diagnosis of Rotating Machinery Relying on Frequency Transforms Time -

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Moradi, Davood | 2011

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 42050 (08)
University: Sharif University of Technology
Department: Mechanical Engineering
Advisor(s): Manzuri, Mohammad Taghi
Abstract:
This thesis presents several methods time-frequency based approach for classifying the vibration signals of rotatery machine. It uses the features extracted from the time-frequency distribution (TFD) of the vibration signal segments. Results of applying the method to a database of real signals reveal that, for the given classification task, the selected features consistently exhibit a high degree of discrimination between the vibration signals collected from healthy and fault machine. A comparison between the performances of the features extracted from several TFDs shows that the STFT slightly outperforms other reduced interference TFDs.
Keywords:
Diagnosis ; Neural Network ; Vibration ; Support Vector Machine (SVM) ; Time Frequency Transform

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