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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 vibration mechanism of the gearbox and the characteristics and methods of fault diagnosis are analyzed. The basic theory of lifting wavelet is introduced. The lifting wavelet is used to denoise, decompose, reconstruct and extract the power spectrum of the gearbox condition signal. The BP neural network model is used to identify the operating status of the gearbox and locate the fault type and location.