BASED ON NEURAL NETWORK RELIABILITY STUDY OF SHEARER’S CUTTING PART
Roller is an important task of the coal winning machine cutting coal institutions,its structure and motion parameters will directly affect the working efficiency and working reliability of coal winning machine.Based on virtual prototype technology coal winning machine the coupled model is establishe...
| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Strength
2018-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2018.04.018 |
| _version_ | 1826871610293878784 |
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| author | ZHAO LiJuan FAN JiaYi |
| author_facet | ZHAO LiJuan FAN JiaYi |
| author_sort | ZHAO LiJuan |
| collection | DOAJ |
| description | Roller is an important task of the coal winning machine cutting coal institutions,its structure and motion parameters will directly affect the working efficiency and working reliability of coal winning machine.Based on virtual prototype technology coal winning machine the coupled model is established,through dynamic simulation of coal winning machine equivalent stress values of key parts;Simulation different drum rotating speed,drawing speed,cylinder helix Angle,and the cutting line spacing they cut the shell and the equivalent stress value of planet carrier,the roller structure and motion parameters on reliability of key parts of coal winning machine cutting part influence trend;Combined with neural network technology,with different roller structure and motion parameters of the equivalent stress of key parts of coal winning machine values as the neural network training sample,the helix Angle of optimization design,stress value of key parts in the hour of cylinder helix Angle.The research for the drum more accurate theoretical foundation for the selection of structure and motion parameters,has certain engineering application value. |
| first_indexed | 2024-03-12T20:44:20Z |
| format | Article |
| id | doaj.art-9f88c37d5c91401d9b9821cb2729520d |
| institution | Directory Open Access Journal |
| issn | 1001-9669 |
| language | zho |
| last_indexed | 2025-02-16T23:43:21Z |
| publishDate | 2018-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj.art-9f88c37d5c91401d9b9821cb2729520d2025-01-15T02:31:34ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692018-01-014086987430602132BASED ON NEURAL NETWORK RELIABILITY STUDY OF SHEARER’S CUTTING PARTZHAO LiJuanFAN JiaYiRoller is an important task of the coal winning machine cutting coal institutions,its structure and motion parameters will directly affect the working efficiency and working reliability of coal winning machine.Based on virtual prototype technology coal winning machine the coupled model is established,through dynamic simulation of coal winning machine equivalent stress values of key parts;Simulation different drum rotating speed,drawing speed,cylinder helix Angle,and the cutting line spacing they cut the shell and the equivalent stress value of planet carrier,the roller structure and motion parameters on reliability of key parts of coal winning machine cutting part influence trend;Combined with neural network technology,with different roller structure and motion parameters of the equivalent stress of key parts of coal winning machine values as the neural network training sample,the helix Angle of optimization design,stress value of key parts in the hour of cylinder helix Angle.The research for the drum more accurate theoretical foundation for the selection of structure and motion parameters,has certain engineering application value.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2018.04.018ShearerDrumReliabilityNeural networkOptimization design |
| spellingShingle | ZHAO LiJuan FAN JiaYi BASED ON NEURAL NETWORK RELIABILITY STUDY OF SHEARER’S CUTTING PART Jixie qiangdu Shearer Drum Reliability Neural network Optimization design |
| title | BASED ON NEURAL NETWORK RELIABILITY STUDY OF SHEARER’S CUTTING PART |
| title_full | BASED ON NEURAL NETWORK RELIABILITY STUDY OF SHEARER’S CUTTING PART |
| title_fullStr | BASED ON NEURAL NETWORK RELIABILITY STUDY OF SHEARER’S CUTTING PART |
| title_full_unstemmed | BASED ON NEURAL NETWORK RELIABILITY STUDY OF SHEARER’S CUTTING PART |
| title_short | BASED ON NEURAL NETWORK RELIABILITY STUDY OF SHEARER’S CUTTING PART |
| title_sort | based on neural network reliability study of shearer s cutting part |
| topic | Shearer Drum Reliability Neural network Optimization design |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2018.04.018 |
| work_keys_str_mv | AT zhaolijuan basedonneuralnetworkreliabilitystudyofshearerscuttingpart AT fanjiayi basedonneuralnetworkreliabilitystudyofshearerscuttingpart |