CAJ | 학술논문

针对滚动轴承故障检测的问题，提出一种基于小波包能量谱-稀疏核主元的滚动轴承故障检测方法。对振动信号进行小波包分解，提取信号的能量频谱，用增量式样本基构造方法，提取能量频谱的样本基，以此样本基建立核主元模型，来分析轴承振动信号能量频谱的变化。通过实验仿真来说明此算法的有效性。
침대곤동축승고장검측적문제，제출일충기우소파포능량보-희소핵주원적곤동축승고장검측방법。대진동신호진행소파포분해，제취신호적능량빈보，용증량식양본기구조방법，제취능량빈보적양본기，이차양본기건립핵주원모형，래분석축승진동신호능량빈보적변화。통과실험방진래설명차산법적유효성。
For the problem of rolling bearing fault detection, a method of rolling bearing fault detection is proposed, which is based on wavelet packet energy spectrum and sparse kernel principal component. The vibration signal is decomposed by wavelet packet, in order to extract the energy spectrum of the signal. Then the sample base of energy spectrum is extracted through the method of incremental sample base. A kernel principal component model is built by the sample base for the analysis of the energy spectrum of the bearing vibration signal. The experimental simulation is presented to illustrate the effectiveness of the algorithm.