• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2026, Vol. 62 ›› Issue (12): 22-32.doi: 10.3901/JME.260479

• 特邀专栏:数字孪生赋能的高端装备智能运维 • 上一篇    

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考虑周期性冲击的机器人谐波减速器加速退化建模与可靠性评估

王嘉1,2,3, 尹慧强1,2, 王崇帅1,2, 韩旭1,2,3   

  1. 1. 河北工业大学智能配用电装备与系统全国重点实验室 天津 300401;
    2. 河北工业大学电气工程学院 天津 300401;
    3. 河北工业大学机械工程学院 天津 300401
  • 收稿日期:2025-07-25 修回日期:2026-03-02 发布日期:2026-08-03
  • 作者简介:王嘉,女,1988年出生,研究员,博士研究生导师。主要研究方向为机器人可靠性评估、复杂装备可靠性设计等。E-mail:jwangno1@163.com
    尹慧强,男,1999年出生,博士研究生。主要研究方向为工业机器人关节可靠性建模与估计。E-mail:yinhuiqiang2024@stu.hebut.edu.cn
    王崇帅,男,1991年出生,副教授,硕士研究生导师。主要研究方向为谐波减速器动力学建模与可靠性设计。E-mail:wangchongshuai@hebut.edu.cn
    韩旭(通信作者),男,1968年出生,教授,博士研究生导师。主要研究方向为复杂装备可靠性设计方法。E-mail:xhan@hebut.edu.cn
  • 基金资助:
    国家科技重大专项(2026ZD1609306)、国家自然科学基金(52405260)、京津冀基础研究合作专项(E2024202261)和河北省教育厅科学研究(BJK2023031)资助项目。

Accelerated Degradation Modeling and Reliability Estimation for Harmonic Drives in Industrial Robots Considering Periodic Shocks

WANG Jia1,2,3, YIN Huiqiang1,2, WANG Chongshuai1,2, HAN Xu1,2,3   

  1. 1. State Key Laboratory of Smart Power Distribution Equipment and System, Hebei University of Technology, Tianjin 300401;
    2. School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401;
    3. School of Electrical Engineering, Hebei University of Technology, Tianjin 300401
  • Received:2025-07-25 Revised:2026-03-02 Published:2026-08-03

摘要: 工业机器人谐波减速器可靠性评估的准确性一定程度上依赖于加速退化模型对真实服役工况的复现能力以及加速退化试验方法的合理性。然而,现有加速退化模型和试验方法未充分考虑工业机器人用谐波减速器在变速变载、急停急启等工况下所承受的周期性冲击载荷作用,难以准确表征其真实退化过程,影响可靠性评估结果的准确性和可信度。为此,建立了一种考虑周期性冲击载荷的谐波减速器加速退化模型,该模型在Wiener过程中引入周期性阶跃冲击,以刻画机器人重复执行任务过程的启停冲击所引起的减速器性能突变,通过在幂律加速模型中引入冲击影响因子建立冲击载荷与退化速率之间的关联,并基于加速因子不变原则构建了加速退化模型。为保证模型精度,融合拉丁超立方采样与遗传算法进行高维非线性参数估计,获得模型参数95%置信区间;基于工业机器人实测载荷谱数据,提出服役载荷谱驱动的加速退化试验方法,结合当量扭矩一致性原则编制多级加速加载谱,以模拟变速变载及冲击环境;最后,对三台相同谐波减速器开展加速退化试验,获取传动误差退化数据并进行可靠性评估。结果表明,所提模型相较于现有模型具有更高的可靠性评估精度,能够更准确地预测谐波减速器服役寿命。

关键词: 加速退化试验, 工业机器人, 加速退化模型, 可靠性评估, 谐波减速器

Abstract: The accuracy of reliability assessment for harmonic drives in industrial robots depends on the extent to which accelerated degradation models (ADMs) can reflect actual service conditions and on the validity of accelerated degradation testing methods. However, existing ADMs and test methods often fail to adequately characterize the periodic shock loads experienced by harmonic drives under complex operating conditions, such as variable speed and load, forward-reverse switching, and abrupt starts and stops. As a result, the degradation behavior of harmonic drives is difficult to characterize accurately, which undermines the credibility of reliability assessment results. To address this issue, this study develops a novel ADM for harmonic drives that explicitly incorporates periodic shock loads. Periodic step shocks are introduced into a Wiener process to capture abrupt performance changes induced by shocks during operating-condition transitions. In addition, a shock influence factor is incorporated into a power-law acceleration model to establish the relationship between shock loads and degradation rate, and the resulting ADM is formulated based on the acceleration factor constant principle. To ensure model accuracy, a hybrid parameter estimation approach combining Latin hypercube sampling and a genetic algorithm is employed for high-dimensional nonlinear estimation, and the 95% confidence intervals of the model parameters are obtained. Furthermore, a service load spectrum-driven accelerated degradation testing method is proposed based on measured load spectrum data from industrial robots. Following the principle of equivalent torque consistency, a multi-level accelerated loading spectrum is designed to simulate variable-speed, variable-load, and shock conditions. Accelerated degradation tests are then conducted on three harmonic drives to obtain transmission error degradation data for reliability assessment. The results show that the proposed model provides higher reliability assessment accuracy than existing models and enables more accurate prediction of the service life of harmonic drives.

Key words: accelerated degradation test, industrial robot, accelerated degradation model, reliability estimation, harmonic drive

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