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- Title
METALLURGICAL PRODUCTIONS FAULT DETECTION METHOD BASED ON RESLSTM-CNN MODEL.
- Authors
CHEN, Z. J.; ZHAO, J.; LIU, M. A.
- Abstract
Timely detection of abnormal working conditions and accurate diagnosis of abnormal working conditions are of great research significance to ensure the safe and stable operation of metallurgical production processes and to avoid losses caused by faults. In this paper, it propose a residual long and short-term memory network and convolutional neural network (RESLSTM-CNN) model for fault detection in metallurgical production processes bearing fault detection with an accuracy of 98,92 %.
- Subjects
CONVOLUTIONAL neural networks; MANUFACTURING processes
- Publication
Metalurgija, 2023, Vol 62, Issue 2, p247
- ISSN
0543-5846
- Publication type
Article