摘要
对齿轮箱的振动机理以及故障诊断特点、方法进行分析,介绍了提升小波的基本理论。并利用提升小波对齿轮箱工况信号进行消噪、分解、重构以及提取功率谱,采用BP神经网络模型识别齿轮箱运行状态以及定位故障类型和部位。
The thesis analyzes the vibration mechanism of the gearbox and the characteristics and the method of fault diagnosis, and introduces the basic thories of lifting wavelet. The lifting wavelet can be used in the gearbox conditions signal to denoising and decompose and reconstructed as well as extractthe signal power spectrum, the BP neural networks model can be used in the gearbox singnal to distinguish the running state and locate the faut type and location.
出处
《煤矿机械》
北大核心
2013年第10期247-249,共3页
Coal Mine Machinery
基金
国家自然科学基金资助项目(50875247)
