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中文摘要：
针对滚动轴承内外圈的早期故障，提出了一种新的诊断方法，该方法融合了数学形态学对非线性信号的滤波和信息熵理论在信号表征方面的优越性。首先，利用数学形态差值滤波器对实测的轴承内外圈轻重损伤的故障信号进行消噪处理，充分突出了有用的故障特征信息；然后，利用差分熵提取该信号中的突变特征信息，对其进行不确定性和复杂性度量；最后，根据突变点的冲击时间间隔和内外圈故障周期性冲击的时间间隔一致的思想来完成对滚动轴承的故障诊断。通过对仿真信号和滚动轴承实测内外圈两种故障程度的振动信号的诊断分析，证明该方法能够很好地识别轴承内外圈早期故障的类型，且具有很高的准确率。
英文摘要：
Concerning the early fault diagnosis oi mner and outer race, a novet metnoa was pro- posed. The method put the advantages of mathematical morphology filtering nonlinear signals and the advantages of information entropy theory characterizing signals together. Firstly, the measured slight and severe fault signals of inner and outer race faults were filtered by morphological difference filter to get more useful fault characteristic informations. Secondly, the abrupt informations of signals were extracted by difference entropy, and the uncertainty and complexity of abrupt information were meas- ured by difference entropy. Lastly, the faults were diagnosed successfully based on the mind of the periodic time interval of abrupt point coincided with the periodic impulsive time interval of inner and outer race faults. The simulation signals and the two fault signals of the rolling bearing were tested and verified, the result is that the new method can diagnosis the early faults of inner and outer race with high accuracy.
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