航空发动机滚动轴承故障特征频率研究

Research on Fault Feature Frequency of Aero-engine Rolling Bearing

航空发动机作为航空飞行器的动力装置,对飞行器安全稳定的运行具有重要的影响。滚动轴承是航空发动机的关键部件,也是较为脆弱、故障频繁发生的易损件,对其进行实时的故障诊断尤为重要。该文利用独立分量方法解析滚动轴承振动混合信号,基于负熵的快速不动点算法将滚动轴承故障振动信号分离,再用包络谱分析故障振动信号与公式计算出的故障特征频率作比较。通过分析,表明这种分析方法能够正确地检测出滚动轴承故障。

As an aerospace vehicle power device,there is an important influence on safety and stability for the aircraft.Rolling bearings,which are key components of the engine,are wearing parts with relatively fragile and frequently fail.Therefore,it is momentous for faults diagnosis of rolling bearings.In order to realize the fault diagnosis of the aero-engine rolling bearing,independent component analysis(ICA)is proposed in this paper.It can separate the mixed vibration signal collected during the rolling bearing test with fast fixed point algorithm based on negative entropy(Fast-ICA),and then compares the fault vibration signal with the frequency of fault characteristic calculated by envelope spectrum analysis.It is shown that this analysis method can detect the malfunction of rolling bearing correctly and efficiently.