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Fault diagnosis of rotation vector reducer for industrial robot based on a convolutional neural network
ID
Yang, Shuai
(
Avtor
),
ID
Luo, Xing
(
Avtor
),
ID
Li, Chuan
(
Avtor
)
PDF - Predstavitvena datoteka,
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MD5: B5EB8FC6FAC45323FB8977A9CE40114D
URL - Izvorni URL, za dostop obiščite
https://www.sv-jme.eu/sl/article/fault-diagnosis-of-rotation-vector-reducer-for-industrial-robot-based-on-convolutional-neural-network/
Galerija slik
Izvleček
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.
Jezik:
Angleški jezik
Ključne besede:
fault diagnosis
,
convolutional neural networks
,
RV reducers
Vrsta gradiva:
Članek v reviji
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FS - Fakulteta za strojništvo
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Leto izida:
2021
Št. strani:
Str. 489-500
Številčenje:
Vol. 67, no. 10
PID:
20.500.12556/RUL-132525
UDK:
681.5:007.52
ISSN pri članku:
0039-2480
DOI:
10.5545/sv-jme.2021.7284
COBISS.SI-ID:
82633475
Datum objave v RUL:
28.10.2021
Število ogledov:
1061
Število prenosov:
164
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Objavi na:
Gradivo je del revije
Naslov:
Strojniški vestnik
Skrajšan naslov:
Stroj. vestn.
Založnik:
Zveza strojnih inženirjev in tehnikov Slovenije [etc.], = Association of Mechanical Engineers and Technicians of Slovenia [etc.
ISSN:
0039-2480
COBISS.SI-ID:
762116
Sekundarni jezik
Jezik:
Slovenski jezik
Naslov:
Diagnosticiranje napak na reduktorjih RV za industrijske robote na osnovi konvolucijske nevronske mreže
Ključne besede:
diagnosticiranje napak
,
konvolucijske nevronske mreže
,
reduktorji RV
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