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Fault diagnosis of rotation vector reducer for industrial robot based on a convolutional neural network
ID
Yang, Shuai
(
Author
),
ID
Luo, Xing
(
Author
),
ID
Li, Chuan
(
Author
)
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https://www.sv-jme.eu/sl/article/fault-diagnosis-of-rotation-vector-reducer-for-industrial-robot-based-on-convolutional-neural-network/
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Abstract
As a key component of a mechanical drive system, the failure of the reducer will usually cause huge economic losses and even lead to serious casualties in extreme cases. To solve this problem, a two-dimensional convolutional neural network (2D-CNN) is proposed for the fault diagnosis of the rotation vector (RV) reducer installed on the industrial robot (IR). The proposed method can automatically extract the features from the data and reduce the connections between neurons and the parameters that need to be trained with its local receptive field, weight sharing, and subsampling features. Due to the aforementioned characteristics, the efficiency of network training is significantly improved, and verified by the experimental simulations. Comparative experiments with other mainstream methods are carried out to further validate the fault classification accuracy of the proposed method. The results indicate that the proposed method out-performs all the selected methods.
Language:
English
Keywords:
fault diagnosis
,
convolutional neural networks
,
RV reducers
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FS - Faculty of Mechanical Engineering
Publication status:
Published
Publication version:
Version of Record
Year:
2021
Number of pages:
Str. 489-500
Numbering:
Vol. 67, no. 10
PID:
20.500.12556/RUL-132525
UDC:
681.5:007.52
ISSN on article:
0039-2480
DOI:
10.5545/sv-jme.2021.7284
COBISS.SI-ID:
82633475
Publication date in RUL:
28.10.2021
Views:
1063
Downloads:
164
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Record is a part of a journal
Title:
Strojniški vestnik
Shortened title:
Stroj. vestn.
Publisher:
Zveza strojnih inženirjev in tehnikov Slovenije [etc.], = Association of Mechanical Engineers and Technicians of Slovenia [etc.
ISSN:
0039-2480
COBISS.SI-ID:
762116
Secondary language
Language:
Slovenian
Title:
Diagnosticiranje napak na reduktorjih RV za industrijske robote na osnovi konvolucijske nevronske mreže
Keywords:
diagnosticiranje napak
,
konvolucijske nevronske mreže
,
reduktorji RV
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