基于振动时域分析的齿轮故障特征提取

Gear Fault Diagnosis Based on Vibration Time-domain Data

螺旋锥齿轮是驱动桥传动链的关键组成部分,也是汽车传动系统的末端核心部件。在驱动桥型式试验中,齿轮疲劳试验占主导地位。前期,由于缺乏故障诊断设备,齿轮疲劳试验大多是在完全丧失传动能力后停止,相应的,螺旋锥齿轮的轮齿严重损毁,导致无法确定疲劳源与疲劳原因。因此,难以制定有效的设计优化方案,导致设计验证工作的反复,以及开发周期和成本的爬升。文章将机械故障诊断原理引入驱动桥齿轮疲劳试验,结合螺旋锥齿轮的啮合原理以及桥壳的传递函数特性,自主开发了适用于驱动桥的齿轮故障在线诊断系统。该系统采用自相关和时域同步平均处理算法,成功实现齿轮故障冲击信号的提取与识别,通过早期预警与主动停机,极大地为齿轮疲劳原因分析提供便利,提升了驱动桥开发效率。另外,随着汽车智能化的发展,驱动桥故障诊断系统可为无人驾驶提供坚定的理论基础与实践基础。

Spiral bevel gear is the key component of drive axle drive chain,and also the end core component of automobile transmission system.In the driving bridge type test,the gear fatigue test plays a dominant role.In the early stage,due to the lack of fault diagnosis equipment,most gear fatigue tests were stopped after the complete loss of transmission capacity.Accordingly,the gear teeth of spiral bevel gears were seriously damaged,which made it impossible to determine the fatigue source and cause.Therefore,it is difficult to formulate an effective design optimization scheme,which leads to repeated design verification work and climbing of development cycle and cost.In this paper,the mechanical fault diagnosis principle is introduced into the fatigue test of the drive axle gear.Combining the meshing principle of the spiral bevel gear and the transfer function characteristics of the axle housing,the gear fault online diagnosis system for the drive axle is developed independently.The system uses autocorrelation and time-domain synchronous average processing algorithms to successfully extract and identify gear fault impact signals.Through early warning and active shutdown,it greatly facilitates the analysis of gear fatigue causes and improves the development efficiency of drive axle.In addition,with the development of automobile intelligence,the drive axle fault diagnosis system can provide a firm theoretical and practical basis for driverless driving.