动力学模型驱动的RV减速器故障诊断方法

doi:10.3901/JME.2025.11.194

摘要/Abstract

摘要： 基于机器学习对旋转矢量(Rotary vector, RV)减速器进行状态监测，对提高RV减速器的可靠性和安全性具有重要意义。然而，在工程应用中，故障样本缺失是制约人工智能诊断发展的根本原因。为解决RV减速器故障样本不足的问题，提出了基于RV减速器动力学仿真的智能诊断方法。首先，建立正常状态下的RV减速器动力学模型，采用皮尔逊相关系数修正模型，获取较为精确的动力学模型。其次，建立齿轮故障数学模型并添加至正常RV减速器动力学模型中，计算生成故障样本库作为人工智能诊断模型的训练样本，用于待诊断测试样本分类。最后，将仿真得到的故障样本作为训练样本，实验测试得到的未知故障样本作为测试样本，通过卷积神经网络进行故障分类，结果表明：基于RV减速器动力学模型的智能诊断方法可解决故障样本缺失导致分类精度低的问题。

关键词: RV减速器, 动力学模型, 数值模拟, 人工智能, 故障诊断

Abstract: The conditional monitoring of rotary vector (RV) reducers using machine learning has great significance to guarantee the reliability and security of RV reducer. However, in engineering applications, fault samples missing is rationale for restricting the development of artificial intelligence diagnosis. Because the problem of the insufficient fault sample of the RV reducer that have to be resolved, an intelligent diagnosis methods using dynamic model is proposed to detect faults in these reducers. In the first step, dynamic model of the healthy RV reducer is constructed, and pearson correlation coefficient (PCC)-based model updating technique is employed to obtain dynamic model with a certain precision. In the second step, the mathematical model of gear fault is established and inserted into the dynamic model to calculate the fault samples, which served as training samples of artificial intelligence diagnostic models to classify testing samples (fault to be diagnosed). Finally, the simulated fault samples are used as training samples, and the unknown fault samples obtained from test are utilized as test sample, fault classification using convolutional neural network (CNN) are obtained, which show that dynamic model driving fault diagnosis method for RV reducer can be guided to solve fault samples missing problem.

Key words: RV reducer, dynamic model, numerical simulation, artificial intelligent, fault diagnosis

中图分类号:

TP183
TH17

郑俊康, 王辉, 向家伟. 动力学模型驱动的RV减速器故障诊断方法[J]. 机械工程学报, 2025, 61(11): 194-207.

ZHENG Junkang, WANG Hui, XIANG Jiawei. Dynamic Model Driving Fault Diagnosis Method for RV Reducer[J]. Journal of Mechanical Engineering, 2025, 61(11): 194-207.

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