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Degradation and reliability assessment of accuracy life of RV reducers
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Hang XU1, 2, Yixuan NIE1, 2, Dongjie WEN1, 2, Jihua REN3, Zhihui HONG4
Journal of Mechanical Transmission | 2026, 50(1) : 133 - 141
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Journal of Mechanical Transmission | 2026, 50(1): 133-141
• Test·Analysis •
Degradation and reliability assessment of accuracy life of RV reducers
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Hang XU1, 2, Yixuan NIE1, 2, Dongjie WEN1, 2, Jihua REN3, Zhihui HONG4
Affiliations
  • 1.Key Laboratory of Optical Sensing and Testing Technology for Mechanical Industry, Zhongyuan University of Technology, Zhengzhou451191, China
  • 2.School of Intelligent Mechanical and Electrical Engineering（School of Industrial Design）, Zhongyuan University of Technology, Zhengzhou 451191, China］
  • 3.School of Intelligent Manufacturing and Materials Engineering, Gannan University of Science and Technology, Ganzhou341000, China
  • 4.Dongguan Huanli Intelligent Technology Co., Ltd., Dongguan523878, China
Published: 2026-01-15 doi: 10.16578/j.issn.1004.2539.2026.01.017
Outline
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Objective

The 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.

Methods

Taking 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.

Results

The results show that the prediction accuracy based on Gaussian process regression model is significantly better than that of the 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.

RV reducer  /  Accuracy retentivity  /  Gamma process  /  Gaussian process regression  /  Reliability assessment
Hang XU, Yixuan NIE, Dongjie WEN, Jihua REN, Zhihui HONG. Degradation and reliability assessment of accuracy life of RV reducers[J]. Journal of Mechanical Transmission, 2026 , 50 (1) : 133 -141 . DOI: 10.16578/j.issn.1004.2539.2026.01.017
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Article Info
doi: 10.16578/j.issn.1004.2539.2026.01.017
  • Receive Date：2024-09-09
  • Online Date：2026-05-20
  • Published：2026-01-15
Article Data
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History
  • Received：2024-09-09
Affiliations
    1.Key Laboratory of Optical Sensing and Testing Technology for Mechanical Industry, Zhongyuan University of Technology, Zhengzhou451191, China
    2.School of Intelligent Mechanical and Electrical Engineering（School of Industrial Design）, Zhongyuan University of Technology, Zhengzhou 451191, China］
    3.School of Intelligent Manufacturing and Materials Engineering, Gannan University of Science and Technology, Ganzhou341000, China
    4.Dongguan Huanli Intelligent Technology Co., Ltd., Dongguan523878, China
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表12种不同金属材料的力学参数
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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