Fault Diagnosis of Rotating Machinery Based on 1D-2D Joint Convolution Neural Network

Convolutional neural network has been widely used in fault diagnosis of mechanical devices. In particular, a 2-D convolutional neural network requires manual selection of multiscale transformation to transform vibration signal into the 2-D structure. Although a 1-D convolution neural network can dir...

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Vydané v:	IEEE transactions on industrial electronics (1982) Ročník 70; číslo 5; s. 5277 - 5285
Hlavní autori:	Du, Wenliao, Hu, Pengjie, Wang, Hongchao, Gong, Xiaoyun, Wang, Shuangyuan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.05.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Artificial neural networks Back propagation networks Continuous wavelet transforms Convolution Convolutional neural networks Datasets Diagnostic systems Entropy (Information theory) Error propagation Fault diagnosis Feature extraction Gearboxes joint convolutional neural network (JCNN) Mechanical devices Neural networks Rotating machinery Signal processing Transforms Two dimensional models Vibration Vibrations Worm gears
ISSN:	0278-0046, 1557-9948
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