Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine

Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine

Classification is an essential task for many applications, including text classification, image classification, data classification, and so on. The present study investigates the accuracy of different machine learning classification algorithms with three different data smoothing techniques for gas t...

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Bibliographic Details
Main Authors: Alemu Lemma, T. (Author), Ambri Abdul Karim, Z. (Author), Molla Salilew, W. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2022
Subjects:
Classification
Classification (of information)
Computer aided diagnosis
Data handling
Data smoothing
Decision trees
Erosion
Fault detection
Fault detection and isolation
Fouling
Gas turbine
Gas turbine engine
Gas turbines
Gases
Inlet guide vane
Learning algorithms
Learning systems
Machine learning
Machine learning techniques
Machine-learning
Nearest neighbor search
Nearest-neighbour
Performance Modeling
Sensitivity analysis
Smoothing techniques
Support vector machines
Text processing
Turbine components
Variable inlet guide vane
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