基于小波分析的大型回转支承故障特征信号的提取

Extraction of Vibration Signal of Large-scale Bearing Based on Wavelet Analysis

现场的测试及分析发现 ,门座式起重机回转支承的局部损伤及由缺陷类故障所引起的低频振动信号由于受到系统高频固有振动及其他背景噪声的干扰而难以分离 ,小波分析以其良好的时频局部化分析特性 ,弥补了传统信号分析方法如傅立叶变换、短时傅立叶变换等的不足 ,较好地实现了对信号全貌及其局部特性的双重分析 .

From spot test and analyzing, it has been verified that the low frequency signal caused by the fault such as part damage and defect of the large-scale bearing of gantry crane, is difficult to separate from the high-frequency signal caused by the vibration of system and other interference of background noise. Wavelet analysis is of good characteristic of time-frequently localization analysis, which can overcome the shortcoming of traditional signal analysis such as Fourier Transform and short Fourier Transform. A new method based on the wavelet is presented to effectively extract the features of vibration signal of the partial damage and defect information of the device from complicated backgrounds.