Identification of Babbitt Damage and Excessive Clearance in Journal Bearings through an Intelligent Recognition Approach

Journal bearings play an important role on many rotating machines placed on industrial environments, especially in steam turbines of thermoelectric power plants. Babbitt damage (BD) and excessive clearance (C) are usual faults of steam turbine journal bearings. This paper is focused on achieving an...

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Bibliographic Details
Published in:International journal of advanced computer science & applications 2021, Vol.12 (4)
Main Authors: Gómez, Joel Pino, E., Fidel, C., Julio, Villuendas, Yenny
Format: Article
Language:English
Subjects:
Algorithms
Classification
Clearances
Damage detection
Fault detection
Faults
Feature selection
Journal bearings
Pattern recognition
Power plants
Rotating machinery
Rotating machines
Steam electric power generation
Steam turbines
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Summary:Journal bearings play an important role on many rotating machines placed on industrial environments, especially in steam turbines of thermoelectric power plants. Babbitt damage (BD) and excessive clearance (C) are usual faults of steam turbine journal bearings. This paper is focused on achieving an effective identification of these faults through an intelligent recognition approach. The work was carried out through the processing of real data obtained from an industrial environment. In this work, a feature selection procedure was applied in order to choose the features more suitable to identify the faults. This feature selection procedure was performed through the computation of typical testors, which allows working with both quantitative and qualitative features. The classification tasks were carried out by using Nearest Neighbors, Voting Algorithm, Naïve Associative Classifier and Assisted Classification for Imbalance Data techniques. Several performance measures were computed and used in order to assess the classification effectiveness. The achieved results (e.g., six performance measures were above 0.998) showed the convenience of applying pattern recognition techniques to the automatic identification of BD and C.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2021.0120467