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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©2018 Mehrdad Heydarzadeh. All Rights Reserved.