CAJ | 학술논문

针对传统的时域、频域特征不能明显地表征滚动轴承的早期退化特征的问题，提出了一种小波包能量谱结合主成分分析构建综合评估函数的滚动轴承早期性能退化评估方法。该方法以采集到的轴承正常工作时的振动信号作为训练样本，对样本进行小波包能量谱计算，得到高维特征向量；再利用主成分分析方法降维并建立综合评估函数对早期性能退化区的数据进行判断。运用实测的滚动轴承全寿命实验数据进行检验，结果表明该方法能实现对滚动轴承早期性能退化的评估。
침대전통적시역、빈역특정불능명현지표정곤동축승적조기퇴화특정적문제，제출료일충소파포능량보결합주성분분석구건종합평고함수적곤동축승조기성능퇴화평고방법。해방법이채집도적축승정상공작시적진동신호작위훈련양본，대양본진행소파포능량보계산，득도고유특정향량；재이용주성분분석방법강유병건립종합평고함수대조기성능퇴화구적수거진행판단。운용실측적곤동축승전수명실험수거진행검험，결과표명해방법능실현대곤동축승조기성능퇴화적평고。
The traditional time-frequency characteristics was not obvious in the early degradation extraction of the rolling bearings so this paper put forward a method based on wavelet packet energy spectrum in combination with principal component analysis for the early degradation extraction.First using normal signal data the wavelet packet energy spectrum was acquireal,then the principal compo-nent analysis was used to achieve dimension reduction for the high dimensional feature vector.Finally through the principal component analysis the comprehensive evaluation function was constructed, which was used to achieve the early degradation extraction of the rolling bearings.