Helical gear wear monitoring: Modelling and experimental validation
Helical gear wear monitoring: Modelling and experimental validation
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斜齿轮磨损监测：建模和实验验证
DOI：
10.1016/j.mechmachtheory.2017.07.012
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发表时间：
2017-11-01
影响因子：
5.2
通讯作者：
Ball, Andrew D.
中科院分区：
文献类型：
--
作者：
Brethee, Khaldoon F.;Zhen, Dong;Ball, Andrew D.
齿轮齿面磨损是一种常见的失效模式。然而，这种情况会在相对较长的使用时间内发生，它会降低操作效率并导致其他重大故障，例如过度拔齿和灾难性断裂。为了在磨损的早期阶段开发准确的磨损检测和诊断方法，本文通过实验和数值研究检查了随着齿接触表面磨损程度的增加齿轮的动态响应。在运行至故障测试中使用了由背对背两级螺旋齿轮箱装置组成的实验测试设备，其中施加可变正弦和阶跃增量负载以及可变速度，并且允许齿轮磨损自然进行。还开发了一个综合动态模型来研究表面磨损对齿轮动态响应的影响，其中包括基于弹流动力润滑 (EHL) 原理的时变刚度和齿摩擦。该模型由 18 个自由度 (DOF) 振动系统组成，其中包括支撑轴承、驱动电机和加载系统的影响。它还耦合因时变摩擦力、时变网格刚度和不同磨损严重程度的激励而产生的横向和扭转运动。获取由牙齿磨损严重程度和摩擦激励引起的振动特征，用于确定参数并通过实验结果验证模型。实验测试和数值模型结果显示了不同齿轮尺寸和几何形状的明显相关行为。啮合频率分量的谱峰及其边带用于检查磨损引起的响应模式。本文的结论是，二次和三次谐波以及边带分量的啮合振动幅度随着磨损程度的增加而显着增加，因此这些可以作为故障检测和诊断的有效特征。 (C) 2017 Elsevier Ltd. 保留所有权利。
Gear tooth surface wear is a common failure mode. It occurs over relatively long periods of service nonetheless, it degrades operating efficiency and leads to other major failures such as excessive tooth removal and catastrophic breakage. To develop accurate wear detection and diagnosis approaches at the early phase of the wear, this paper examines the gear dynamic responses from both experimental and numerical studies with increasing extents of wear on tooth contact surfaces. An experimental test facility comprising of a back-to-back two-stage helical gearbox arrangement was used in a run-to-failure test, in which variable sinusoidal and step increment loads along with variable speeds were applied and gear wear was allowed to progress naturally. A comprehensive dynamic model was also developed to study the influence of surface wear on gear dynamic response, with the inclusion of time-varying stiffness and tooth friction based on elasto-hydrodynamic lubrication (EHL) principles. The model consists of an 18 degree of freedom (DOF) vibration system, which includes the effects of the supporting bearings, driving motor and loading system. It also couples the transverse and torsional motions resulting from time-varying friction forces, time varying mesh stiffness and the excitation of different wear severities. Vibration signatures due to tooth wear severity and frictional excitations were acquired for the parameter determination and the validation of the model with the experimental results. The experimental test and numerical model results show clearly correlated behaviour, over different gear sizes and geometries. The spectral peaks at the meshing frequency components along with their sidebands were used to examine the response patterns due to wear. The paper concludes that the mesh vibration amplitudes of the second and third harmonics as well as the sideband components increase considerably with the extent of wear and hence these can be used as effective features for fault detection and diagnosis. (C) 2017 Elsevier Ltd. All rights reserved.