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提出了基于加窗线性卡尔曼滤波模型的设备剩余使用寿命预测新方法,明确了应用加窗线性卡尔曼滤波模型进行剩余使用寿命预测的过程。应用试验数据验证了方法的有效性,案例分析结果表明:对于退化指标在前期平稳、后期突变的齿轮箱全寿命试验数据,剩余使用寿命的预测值与实际值在齿轮箱运行的前期相差较大,而在后期则较为相近;通过对退化指标值进行拟合处理,可以明显消除退化指标值波动对剩余使用寿命预测值的影响。
A new method of predicting the remaining life of equipment based on the windowed Kalman filter model is proposed and the process of predicting the remaining life is clarified by using the windowed Kalman filter model. The test results validate the effectiveness of the method. The results of the case study show that the prediction values of the remaining service life and the predicted values of the remaining service life of the gearbox with a steady and late-degenerated degradation index are quite different from the actual values of the gearbox operation , And they are similar at the later stage. By fitting the regression index values, the influence of the degradation index values on the remaining service life prediction can be obviously eliminated.