Performance of Machine-Learning-Based Algorithms for Anomaly Detection in Variable Frequency Drives Using Temperature Signals-Reference-Cited by-同舟云学术

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Performance of Machine-Learning-Based Algorithms for Anomaly Detection in Variable Frequency Drives Using Temperature Signals

Published:2023-08-28 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 14th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED)
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Author:

Surówka Artur D.¹,Tan Ruomu²,Saberi Alireza Nemat³,Firla Marcin¹

Affiliation:

1. ABB Sp. z o.o.,Corporate Technology Center,Kraków,Poland

2. ABB AG,Corporate Research Center,Ladenburg,Germany

3. ABB Oy,Motion System Drives,Helsinki,Finland

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10271381/10271407/10271477.pdf?arnumber=10271477

Reference35 articles.

1. Evaluation of Machine Learning for Sensorless Detection and Classification of Faults in Electromechanical Drive Systems

2. Anomaly detection based on a dynamic Markov model

3. Distributed condition monitoring systems in electric drives manufacturing

4. Deep Learning-Based Time-Series Analysis for Detecting Anomalies in Internet of Things

5. A Study on the Anomaly Detection of Engine Clutch Engagement/Disengagement Using Machine Learning for Transmission Mounted Electric Drive Type Hybrid Electric Vehicles;yonghyeok;Applied Sciences,2021

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