Support vector machine classifier for diagnosis in electrical machines: Application to broken bar

Author:

Matić Dragan,Kulić Filip,Pineda-Sánchez Manuel,Kamenko Ilija

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference33 articles.

1. Multiple discriminate analysis and neural network based monolith and partition fault detection schemes for broken rotor bar in induction motor;Ayhan;IEEE Transactions on Industrial Electronics,2006

2. SVM practical industrial application for mechanical faults diagnostic;Baccarini;Journal of Expert Systems with Applications,2011

3. Quantitative evaluation of induction motor broken bars by means of electrical signature analysis;Bellini;IEEE Transactions on Industry Applications,2001

4. Advances in diagnostic techniques for induction machines;Bellini;IEEE Transactions on Industrial Electronics,2008

5. A review of induction motors signature analysis as a medium for faults detection;Benbouzid;IEEE Transactions on Industrial Electronics,2000

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4. Implementation of Vibrations Faults Monitoring and Detection on Gas Turbine System Based on the Support Vector Machine Approach;Journal of Vibration Engineering & Technologies;2023-06-04

5. Dynamic Eccentricity Faut Diagnosis for Inverter-Fed Induction Motor Using Stator Current Temporal Envelope Estimation;2022 2nd International Conference on Advanced Electrical Engineering (ICAEE);2022-10-29

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