关键词: 非参数估计, 核密度估计, 自适应窗宽, 剩余寿命预测, 故障诊断

Abstract: Due to the lack of fault sample data and similar fault sample data,many existing equipment life predictions often require model structure assumption and parameter estimation,which lead to low accuracy.A real-time residual life prediction method based on kernel density estimation was proposed.In this method,continuous degradation characteristics were used to construct the kernel density estimation model of degraded distribution,and then get the probability distribution function of the residual life.After acquiring the new degenerate feature data,the probability density function was continuously updated by kernel density estimation,and the distribution of residual life was updated.The effectiveness of the proposed method in residual life prediction was verified by an example analysis.

Key words: nonparametric estimation, kernel density estimation, adaptive window width, residual life prediction, fault diagnosis