Cost-efficient real-time condition monitoring and fault diagnostics system for BLDC motor using IoT and Machine learning
Author:
Affiliation:
1. Tallinn University of Technology,Department of Electrical Power Engineering and Mechatronics,Tallinn,Estonia
2. Aalto University,Department of Electrical Engineering and Automation,Espoo,Finland
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9904952/9904955/09905102.pdf?arnumber=9905102
Reference22 articles.
1. Internet based monitoring and control of a wind turbine via PLC
2. Low-Cost SCADA System Using Arduino and Reliance SCADA for a Stand-Alone Photovoltaic System
3. Health monitoring, fault diagnosis and failure prognosis techniques for Brushless Permanent Magnet Machines
4. Bearing Fault Analysis of BLDC Motor for Electric Scooter Application
5. A New Methodology to Estimate the Rotating Phase of a BLDC Motor With Its Application in Variable-Speed Bearing Fault Diagnosis
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1. Machine hearing for predictive maintenance of BLDC motors;Journal of Quality in Maintenance Engineering;2024-09-06
2. Brushless Motor Speed Regulation Using Field Oriented Control Algorithm and IoT;2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS);2023-10-18
3. Machine Learning and Audio Signal Processing for Predictive Maintenance: A review;2023 IEEE 6th Colombian Conference on Automatic Control (CCAC);2023-10-17
4. A Nanosensor-Based Prototype Development for Heavy Metal Detection: A Combined Spectroscopic and Theoretical Study;IEEE Sensors Letters;2023-02
5. Critical Review on Torque Ripple Sources and Mitigation Control Strategies of BLDC Motors in Electric Vehicle Applications;IEEE Access;2023
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