齿轮箱早期的故障信号往往十分微弱,信噪比低,这大大限制了已有诊断方法在早期诊断中的应用,因此如何获取真实的振动信号是提高齿轮箱早期故障诊断质量的关键,独立分量分析(ICA)为此提供了一种新的思路。文

中研究了ICA在齿轮箱故障早期诊断中的应用,首先分析了齿轮箱的混合振动信号模型,然后针对具体的轴承故障进行了实验,并使用快速ICA算法分离出轴承的振动信号-The early gearbox fault signal is often very weak, low signal-to-noise ratio, which greatly limits the application of existing diagnostic methods in the early diagnosis, how to obtain the actual vibration signal is to improve the quality of early gearbox fault diagnosis, independent component analysis (ICA) to provide a new way of thinking. In this paper, the application of the ICA in the early diagnosis of gearbox failure, the first analysis of the the mixed vibration signal model of the gearbox, then conducted experiments for specific bearing failure, isolated bearing vibration signal and use the fast ICA algorithm