摘要
S变换兼具了小波变换和快速傅立叶变换各自的优势,具有良好的时频聚集性。归一化信息熵能够定量地度量信号分布的复杂程度。滚动轴承振动信号经S变换后,利用归一化信息熵定量地度量每个时刻下频率分布均匀程度,提出一种S-时间熵特征指标来反映滚动轴承的退化过程。针对滚动轴承内圈、轴承外圈、轴承滚动体的3种故障,分别对其3种不同损伤程度的数学模型进行仿真数据分析,提取各自S-时间熵指标进行对比,验证该方法的可行性。通过对滚动轴承加速疲劳寿命周期内的数据进行分析,与工程中常用的时域指标有效值进行对比,结果表明该方法的有效性。
The advantages of Wavelet Transform and Fast Fourier Transform(FFT)are obtained by S-Transform.It has excellent time frequency aggregation performance.The complexity of signal distribution was quantified by normalized information entropy.The original vibration signal of the rolling bearing was transformed by S-Transform.The uniformity of frequency distribution was quantified by normalized information entropy at each time.An S-time entropy characteristic index was proposed to reflect the degradation process of rolling bearings.Based on the rolling bearing inner ring and the outer ring of the bearing,bearing three faults were analyzed in 3 different damage degree mathematical model simulation,and extract their S-time entropy index were compared to verify the feasibility of the method.The data of the accelerated fatigue life cycle of the rolling bearing are analyzed and compared with the effective values of the time domain indexes commonly used in the engineering.The results show the effectiveness of the method.
作者
程道来
贾玉琛
潘玉娜
CHENG Daolai;JIA Yuchen;PAN Yuna(School of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, China)
出处
《机床与液压》
北大核心
2019年第19期181-185,共5页
Machine Tool & Hydraulics
基金
上海市科委地方院校能力建设项目(17090503500)
关键词
S变换
S-时间熵
性能退化指标
滚动轴承
S-Transform
S-time entropy
Performance degradation index
Rolling bearings
