Fault diagnosis of industrial robot based on dual-module attention convolutional neural network

Kaijie Lu; Chong Chen; Tao Wang; Lianglun Cheng; Jian Qin

doi:10.1007/s43684-022-00031-5

ScienceGate Book Chapters

JOURNAL ARTICLE

Fault diagnosis of industrial robot based on dual-module attention convolutional neural network

Kaijie Lu Chong Chen Tao Wang Lianglun Cheng Jian Qin

Year: 2022 Journal: Autonomous Intelligent Systems Vol: 2 (1) Publisher: Springer Nature

DOI: 10.1007/s43684-022-00031-5

Get Full-Text PDF Get Analytical Report

Keywords:

Reducer Convolutional neural network Fault (geology) Robot Computer science Dual (grammatical number) Artificial intelligence Artificial neural network Machine learning Engineering

Metrics

Cited By

4.48

FWCI (Field Weighted Citation Impact)

Refs

0.93

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Engineering Diagnostics and Reliability

Physical Sciences → Engineering → Mechanics of Materials

Fault diagnosis of industrial robot based on dual-module attention convolutional neural network

Metrics

Citation History

Topics

Related Documents

A dual attention module and convolutional neural network based bearing fault diagnosis

Motor Fault Diagnosis Based on Convolutional Block Attention Module-Xception Lightweight Neural Network

Fault Diagnosis of Rolling Bearing Based on Convolutional Neural Network of Convolutional Block Attention Module

A Convolutional Block Attention Module Based Lightweight Convolutional Neural Network Model for Rotating Machinery Fault Diagnosis

Fault Diagnosis Method Based on Multi-Attention Convolutional Neural Network