CAJ | 학술논문

微弱信号特征提取对于主轴系统早期故障诊断有着重要意义。从抑制噪声和利用噪声达到提高信噪比的角度出发，基于信号处理领域的研究成果，列举了可用于主轴系统微弱信号特征的提取方法。这些方法包括抑制噪声提高信噪比的信号处理方法和利用噪声增强微弱信号的方法，抑制噪声提高信噪比的信号处理方法有谱峭度、小波变换、经验模式分解、循环平稳理论、盲源分离、流形学习等；利用噪声增强微弱信号的方法有随机共振和总体平均经验模式分解。为主轴故障诊断研究提供了参考。
미약신호특정제취대우주축계통조기고장진단유착중요의의。종억제조성화이용조성체도제고신조비적각도출발，기우신호처리영역적연구성과，열거료가용우주축계통미약신호특정적제취방법。저사방법포괄억제조성제고신조비적신호처리방법화이용조성증강미약신호적방법，억제조성제고신조비적신호처리방법유보초도、소파변환、경험모식분해、순배평은이론、맹원분리、류형학습등；이용조성증강미약신호적방법유수궤공진화총체평균경험모식분해。위주축고장진단연구제공료삼고。
The feature extraction of weak signal is of important significance for early stage fault diagnosis in spindle system. Started from the aspects of suppressing and adding noise to improve the signal to noise ratio,feature extraction methods with weak sig-nal of spindle system using were listed based on the research results of signal processing field. These methods of signal processing are included,to improve the ratio of signal to noise to suppressing noise and using noise to strengthen weak signal. The methods of sup-pressing noise are Spectral Kurtosis,Empirical Mode Decomposition,Wavelet Transform,Cyclostationarity,Blind Source Separa-tion,and Manifold Learning etc. The methods of strengthening weak signal by adding noise are Stochastic Resonance and Ensemble Empirical Mode Decomposition. References are provided for research of spindle fault diagnosis.