关键词: 回转支承, 寿命状态识别, 模糊C均值, 性能退化, 故障诊断

Abstract: To research the life state of slewing bearing for keeping machine work efficiently and stably,an algorithm by combining point density function with Fuzzy C-Means (FCM) which improved classification accuracy and calculation speed was proposed.An experiment on the full life test of slewing bearing was conducted based on the test platform to verify the effectiveness of improved method.The traditional FCM was used for comparison,and the results indicated that the proposed method could recognize the life state of slewing bearing more accurately,which laid the foundation of real-time maintenance.

Key words: slewing bearing, life state recognition, fuzzy C-means, performance degeneration, fault diagnosis