Fault Diagnosis and Prognosis in Industrial Systems Using Machine Learning Techniques

Date

2018-05

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Abstract

This dissertation concerns the development and usage of advanced machine learning and signal processing methods for fault diagnosis and prognosis in industrial systems. It establishes a mathematical framework for detecting and predicting faults in industrial systems.

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Keywords

Machine learning, Signal processing, Bayesian statistical decision theory, Wavelets (Mathematics)

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Rights

©2018 Mehrdad Heydarzadeh. All Rights Reserved.

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