Degradation and reliability assessment of accuracy life of RV reducers
ObjectiveThe industrial robot industry has put forward higher requirements for RV reducers, and the precision life reflects the ability of the reducer to maintain transmission accuracy, which is one of the most important design criteria and usage indicators. To improve the precision performance of p...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2025-01-01
|
| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails?columnId=80338411&Fpath=home&index=0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832595474594398208 |
|---|---|
| author | XU Hang NIE Yixuan WEN Dongjie REN Jihua HONG Zhihui |
| author_facet | XU Hang NIE Yixuan WEN Dongjie REN Jihua HONG Zhihui |
| author_sort | XU Hang |
| collection | DOAJ |
| description | ObjectiveThe industrial robot industry has put forward higher requirements for RV reducers, and the precision life reflects the ability of the reducer to maintain transmission accuracy, which is one of the most important design criteria and usage indicators. To improve the precision performance of precision reducers, it is crucial to evaluate their reliability. Therefore, the degradation characteristics of precision reducers were analyzed.MethodsTaking the RV80E reducer as an example, a random degradation model based on Gamma process was proposed. Combined with the performance degradation data of the reducer transmission accuracy, the model parameters were estimated based on the matrix method and the maximum likelihood estimation method. A Gaussian process regression model optimized by genetic algorithm was established using vibration characteristic data to optimize the prediction of transmission accuracy.ResultsThe results show that the prediction accuracy based on Gaussian process regression model is significantly better than that of traditional regression model. The posterior distribution parameters of the random degradation model are updated by using the algorithm to predict the results, which can effectively evaluate the reliability of the accuracy life of RV reducer and lay the foundation for further reliability optimization design of accuracy life. |
| format | Article |
| id | doaj-art-6ed431452b8c4286856ccb8120b367ae |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2025-01-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-6ed431452b8c4286856ccb8120b367ae2025-01-18T19:00:13ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392025-01-011980338411Degradation and reliability assessment of accuracy life of RV reducersXU HangNIE YixuanWEN DongjieREN JihuaHONG ZhihuiObjectiveThe industrial robot industry has put forward higher requirements for RV reducers, and the precision life reflects the ability of the reducer to maintain transmission accuracy, which is one of the most important design criteria and usage indicators. To improve the precision performance of precision reducers, it is crucial to evaluate their reliability. Therefore, the degradation characteristics of precision reducers were analyzed.MethodsTaking the RV80E reducer as an example, a random degradation model based on Gamma process was proposed. Combined with the performance degradation data of the reducer transmission accuracy, the model parameters were estimated based on the matrix method and the maximum likelihood estimation method. A Gaussian process regression model optimized by genetic algorithm was established using vibration characteristic data to optimize the prediction of transmission accuracy.ResultsThe results show that the prediction accuracy based on Gaussian process regression model is significantly better than that of traditional regression model. The posterior distribution parameters of the random degradation model are updated by using the algorithm to predict the results, which can effectively evaluate the reliability of the accuracy life of RV reducer and lay the foundation for further reliability optimization design of accuracy life.http://www.jxcd.net.cn/thesisDetails?columnId=80338411&Fpath=home&index=0RV reducerAccuracy retentivityGamma processGaussian process regressionReliability assessment |
| spellingShingle | XU Hang NIE Yixuan WEN Dongjie REN Jihua HONG Zhihui Degradation and reliability assessment of accuracy life of RV reducers Jixie chuandong RV reducer Accuracy retentivity Gamma process Gaussian process regression Reliability assessment |
| title | Degradation and reliability assessment of accuracy life of RV reducers |
| title_full | Degradation and reliability assessment of accuracy life of RV reducers |
| title_fullStr | Degradation and reliability assessment of accuracy life of RV reducers |
| title_full_unstemmed | Degradation and reliability assessment of accuracy life of RV reducers |
| title_short | Degradation and reliability assessment of accuracy life of RV reducers |
| title_sort | degradation and reliability assessment of accuracy life of rv reducers |
| topic | RV reducer Accuracy retentivity Gamma process Gaussian process regression Reliability assessment |
| url | http://www.jxcd.net.cn/thesisDetails?columnId=80338411&Fpath=home&index=0 |
| work_keys_str_mv | AT xuhang degradationandreliabilityassessmentofaccuracylifeofrvreducers AT nieyixuan degradationandreliabilityassessmentofaccuracylifeofrvreducers AT wendongjie degradationandreliabilityassessmentofaccuracylifeofrvreducers AT renjihua degradationandreliabilityassessmentofaccuracylifeofrvreducers AT hongzhihui degradationandreliabilityassessmentofaccuracylifeofrvreducers |