RELIABILITY ANALYSIS OF OUTPUT SHAFT OF CUTTING EDGE UNDER RANDOM LOAD
With the "MG2×100/455-BWD" new type of thin coal seam shearer cutting project as the object, its key parts which include the output shaft, shell, carrier load situation have been depth analyzed. Considering the number of loads, the dynamic reliability model of each key part failure mode wh...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2019-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.04.016 |
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| author | ZHAO LiJuan JIN YuJi HUANG Kai |
| author_facet | ZHAO LiJuan JIN YuJi HUANG Kai |
| author_sort | ZHAO LiJuan |
| collection | DOAJ |
| description | With the "MG2×100/455-BWD" new type of thin coal seam shearer cutting project as the object, its key parts which include the output shaft, shell, carrier load situation have been depth analyzed. Considering the number of loads, the dynamic reliability model of each key part failure mode which Based on the reliability interference theory of stress-intensity distribution is established to calculate and analyze its reliability. By Compiling miner load samples with MATLAB, building Solid modeling with Pro/E, generating key parts Flexible body with ANSYS, the rigid and flexible coupling model of the shearing part of the shearer was established and the simulation was carried out by using the special interface MECHANISM/Pro to import ADAMS to get the stress information of the key parts under different working conditions. Taking condition parameters as neural network training samples, the neural network and the virtual prototyping technology are combined to predict the stress under other working conditions, which reduces the simulation time and the workload of the virtual prototype. The research in the paper provides the basis for the design of the shearer, improves its dynamic reliability, shortens the product design cycle, has important theoretical significance and high application value. |
| format | Article |
| id | doaj-art-9954f145ad47466ebacba2c568a45ec2 |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2019-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-9954f145ad47466ebacba2c568a45ec22025-01-15T02:29:28ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692019-01-014186487030605207RELIABILITY ANALYSIS OF OUTPUT SHAFT OF CUTTING EDGE UNDER RANDOM LOADZHAO LiJuanJIN YuJiHUANG KaiWith the "MG2×100/455-BWD" new type of thin coal seam shearer cutting project as the object, its key parts which include the output shaft, shell, carrier load situation have been depth analyzed. Considering the number of loads, the dynamic reliability model of each key part failure mode which Based on the reliability interference theory of stress-intensity distribution is established to calculate and analyze its reliability. By Compiling miner load samples with MATLAB, building Solid modeling with Pro/E, generating key parts Flexible body with ANSYS, the rigid and flexible coupling model of the shearing part of the shearer was established and the simulation was carried out by using the special interface MECHANISM/Pro to import ADAMS to get the stress information of the key parts under different working conditions. Taking condition parameters as neural network training samples, the neural network and the virtual prototyping technology are combined to predict the stress under other working conditions, which reduces the simulation time and the workload of the virtual prototype. The research in the paper provides the basis for the design of the shearer, improves its dynamic reliability, shortens the product design cycle, has important theoretical significance and high application value.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.04.016Output shaft reliability analysisCollaborative simulationDynamic reliabilityNeural Networks |
| spellingShingle | ZHAO LiJuan JIN YuJi HUANG Kai RELIABILITY ANALYSIS OF OUTPUT SHAFT OF CUTTING EDGE UNDER RANDOM LOAD Jixie qiangdu Output shaft reliability analysis Collaborative simulation Dynamic reliability Neural Networks |
| title | RELIABILITY ANALYSIS OF OUTPUT SHAFT OF CUTTING EDGE UNDER RANDOM LOAD |
| title_full | RELIABILITY ANALYSIS OF OUTPUT SHAFT OF CUTTING EDGE UNDER RANDOM LOAD |
| title_fullStr | RELIABILITY ANALYSIS OF OUTPUT SHAFT OF CUTTING EDGE UNDER RANDOM LOAD |
| title_full_unstemmed | RELIABILITY ANALYSIS OF OUTPUT SHAFT OF CUTTING EDGE UNDER RANDOM LOAD |
| title_short | RELIABILITY ANALYSIS OF OUTPUT SHAFT OF CUTTING EDGE UNDER RANDOM LOAD |
| title_sort | reliability analysis of output shaft of cutting edge under random load |
| topic | Output shaft reliability analysis Collaborative simulation Dynamic reliability Neural Networks |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.04.016 |
| work_keys_str_mv | AT zhaolijuan reliabilityanalysisofoutputshaftofcuttingedgeunderrandomload AT jinyuji reliabilityanalysisofoutputshaftofcuttingedgeunderrandomload AT huangkai reliabilityanalysisofoutputshaftofcuttingedgeunderrandomload |