Abstract:

Based on the self-similarity in vibration time series of gearboxes, local scaling analysis is developed to extract the weak information in vibration signals. Combining local scaling exponents and Principal Component Analysis(PCA), low dimensional principal components of local scaling exponents statistics are used to monitor the conditions of gearboxes. Experimental results indicate the proposed method has high efficiency and correct rate on gearbox condition monitoring.

Key words: scaling exponent, Local Scaling Analysis(LSA), Principal Component Analysis(PCA), gearbox, condition monitoring

摘要：

利用齿轮箱振动信号的自相似性，以局域标度分析算法提取齿轮箱振动信号中包含的微弱设备状态特征信息，将局域标度指数与主成分分析法相结合，通过提取局域标度指数多元统计量的低维主分量对齿轮箱状态进行监测。实验结果证明，该方法具有较高的检测效率和准确识别率。

关键词: 标度指数, 局域标度分析, 主成分分析, 齿轮箱, 状态监测

CLC Number: 

• TP206