An Accuracy Prediction Method of the RV Reducer to Be Assembled Considering Dendritic Weighting Function
There are many factors affecting the assembly quality of rotate vector reducer, and the assembly quality is unstable. Matching is an assembly method that can obtain high-precision products or avoid a large number of secondary rejects. Selecting suitable parts to assemble together can improve the tra...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/19/7069 |
| _version_ | 1797479626098868224 |
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| author | Shousong Jin Yanxi Chen Yiping Shao Yaliang Wang |
| author_facet | Shousong Jin Yanxi Chen Yiping Shao Yaliang Wang |
| author_sort | Shousong Jin |
| collection | DOAJ |
| description | There are many factors affecting the assembly quality of rotate vector reducer, and the assembly quality is unstable. Matching is an assembly method that can obtain high-precision products or avoid a large number of secondary rejects. Selecting suitable parts to assemble together can improve the transmission accuracy of the reducer. In the actual assembly of the reducer, the success rate of one-time selection of parts is low, and “trial and error assembly” will lead to a waste of labor, time cost, and errors accumulation. In view of this situation, a dendritic neural network prediction model based on mass production and practical engineering applications has been established. The size parameters of the parts that affected transmission error of the reducer were selected as influencing factors for input. The key performance index of reducer was transmission error as output index. After data standardization preprocessing, a quality prediction model was established to predict the transmission error. The experimental results show that the dendritic neural network model can realize the regression prediction of reducer mass and has good prediction accuracy and generalization capability. The proposed method can provide help for the selection of parts in the assembly process of the RV reducer. |
| first_indexed | 2024-03-09T21:48:29Z |
| format | Article |
| id | doaj.art-f2ef78763d38457ab1938c63b75b8356 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T21:48:29Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-f2ef78763d38457ab1938c63b75b83562023-11-23T20:12:34ZengMDPI AGEnergies1996-10732022-09-011519706910.3390/en15197069An Accuracy Prediction Method of the RV Reducer to Be Assembled Considering Dendritic Weighting FunctionShousong Jin0Yanxi Chen1Yiping Shao2Yaliang Wang3School of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaSchool of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaSchool of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaSchool of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaThere are many factors affecting the assembly quality of rotate vector reducer, and the assembly quality is unstable. Matching is an assembly method that can obtain high-precision products or avoid a large number of secondary rejects. Selecting suitable parts to assemble together can improve the transmission accuracy of the reducer. In the actual assembly of the reducer, the success rate of one-time selection of parts is low, and “trial and error assembly” will lead to a waste of labor, time cost, and errors accumulation. In view of this situation, a dendritic neural network prediction model based on mass production and practical engineering applications has been established. The size parameters of the parts that affected transmission error of the reducer were selected as influencing factors for input. The key performance index of reducer was transmission error as output index. After data standardization preprocessing, a quality prediction model was established to predict the transmission error. The experimental results show that the dendritic neural network model can realize the regression prediction of reducer mass and has good prediction accuracy and generalization capability. The proposed method can provide help for the selection of parts in the assembly process of the RV reducer.https://www.mdpi.com/1996-1073/15/19/7069RV reducerassembly qualitydendritesneural networktransmission accuracy |
| spellingShingle | Shousong Jin Yanxi Chen Yiping Shao Yaliang Wang An Accuracy Prediction Method of the RV Reducer to Be Assembled Considering Dendritic Weighting Function Energies RV reducer assembly quality dendrites neural network transmission accuracy |
| title | An Accuracy Prediction Method of the RV Reducer to Be Assembled Considering Dendritic Weighting Function |
| title_full | An Accuracy Prediction Method of the RV Reducer to Be Assembled Considering Dendritic Weighting Function |
| title_fullStr | An Accuracy Prediction Method of the RV Reducer to Be Assembled Considering Dendritic Weighting Function |
| title_full_unstemmed | An Accuracy Prediction Method of the RV Reducer to Be Assembled Considering Dendritic Weighting Function |
| title_short | An Accuracy Prediction Method of the RV Reducer to Be Assembled Considering Dendritic Weighting Function |
| title_sort | accuracy prediction method of the rv reducer to be assembled considering dendritic weighting function |
| topic | RV reducer assembly quality dendrites neural network transmission accuracy |
| url | https://www.mdpi.com/1996-1073/15/19/7069 |
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