【作者】 陈晓平； 和卫星； 陈季云；

【Author】 Chen Xiaoping He Weixing chen Jiyun (School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013)

【机构】 江苏大学电气信息工程学院；

【摘要】 利用小波阈值消噪技术和小波包特征提取方法,对石油钻井台3524型传动滚动轴承振动信号进行处理,大幅度提高了信噪比,使得轴承损伤造成的冲击突变信号得以突出,提高了特征信息的灵敏度和分辨率,从而达到有效提取滚动轴承信号特征与故障识别的目的。通过大量实际数据处理和统计结果表明,该方法在滚动轴承振动信号处理和故障诊断中具有显著作用。更多还原

【Abstract】 Using wavelet threshold technique for noise reducing and wavelet package method for feature extraction, the vibration signals of power transmission rolling bearing of type 3524 in oil drilling platform are processed making the signal-to-noise ratio significantly increased and the bearing fault caused abrupt impulse waves enhanced. With this method,the sensitivity and the resolution of the character information are improved so that the working state features of the roiling bearings are extracted efficiently and the purpose for fault recognition is realized.Large amount real data processing result and the statistics show that this method is efficiency in rolling bearing vibration signal processing and fault diagnoses applications.更多还原