Fault diagnosis of natural gas pipeline leakage based on 1D-CNN and self-attention mechanism
Author:
Affiliation:
1. School of electrical engineering, Chongqing University of Science and Technology,Chongqing,China
2. College of Physics and Electronic Engineering, Chongqing Normal University,Chongqing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9929429/9929329/09930063.pdf?arnumber=9930063
Reference9 articles.
1. Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)
2. Leak detection of pipeline: An integrated approach of rough set theory and artificial bee colony trained SVM
3. Novel Leakage Detection by Ensemble CNN-SVM and Graph-Based Localization in Water Distribution Systems
4. A novel method based on deep transfer unsupervised learning network for bearing fault diagnosis under variable working condition of unequal quantity
5. A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings
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