CAJ | 학술논문

试验采集的传动箱振动信号特征能量通常很小且易淹没在背景噪声之中，针对这一问题，提出了一种将固有时间尺度分解（Intrinsic Time-scale Decomposition，ITD）与奇异谱分析（Singular Spectrum Analysis，SSA）相结合的时频分析方法，并用于信号微弱特征的提取。通过仿真信号及试验采集的振动信号进行验证，结果表明：该方法能够有效地从混杂着能量较大的背景信号和噪声干扰中提取出微弱信号的特征频率成分，并达到了很好的降噪效果，提取出的信号更接近于原始无噪声信号。研究为设备运行状态信息的提取与状态识别提供了一种新方法。
시험채집적전동상진동신호특정능량통상흔소차역엄몰재배경조성지중，침대저일문제，제출료일충장고유시간척도분해（Intrinsic Time-scale Decomposition，ITD）여기이보분석（Singular Spectrum Analysis，SSA）상결합적시빈분석방법，병용우신호미약특정적제취。통과방진신호급시험채집적진동신호진행험증，결과표명：해방법능구유효지종혼잡착능량교대적배경신호화조성간우중제취출미약신호적특정빈솔성분，병체도료흔호적강조효과，제취출적신호경접근우원시무조성신호。연구위설비운행상태신식적제취여상태식별제공료일충신방법。
Aiming at the problem that characteristic energy of gearbox vibration signal collected in test is usually low and easy to be drown in background noise,a time-frequency domain analysis method based on Intrinsic Time-scale Decomposition(ITD)and Singular Spectrum Analysis (SSA)is proposed to extract the weak characteristic of signals.The method is verified by using simulation signals and vibration signals collected in test.The results show that the method can effectively extract the frequency features from the weak signals mixed with large-energy-background signal and noise,and the noise is reduced effectively, the extracted signals are close to the original noise free signals.The proposed technique develops a novel method to extract status information and recognize the state of equipment in running state.