Modeling and Fault Detection of Brushless Direct Current Motor by Deep Learning Sensor Data Fusion

Modeling and Fault Detection of Brushless Direct Current Motor by Deep Learning Sensor Data Fusion

Only with new sensor concepts in a network, which go far beyond what the current state-of-the-art can offer, can current and future requirements for flexibility, safety, and security be met. The combination of data from many sensors allows a richer representation of the observed phenomenon, e.g., sy...

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Bibliographic Details
Main Authors: Huebner, M. (Author), Jongmanns, M. (Author), Meisel, T. (Author), Reichenbach, M. (Author), Suawa, P. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
accelerometer
Accelerometers
Brain
brushless direct current motor
Brushless direct current motor
Convolution
Convolutional neural networks
'current
Data mining
Decision making
deep convolutional neural networks
deep learning sensor fusion
Deep learning sensor fusion
Deep neural networks
Extraction
Fault detection
faults detection
Faults detection
Feature extraction
Learning methods
long short-term memory
Long short-term memory
microphone
Microphones
Predictive maintenance
Sensor concepts
Sensor fusion
Sensors data fusion
State of the art
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