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中文摘要：
根据实际机械生产过程中设备的全寿命数据集不易获取以及性能退化数据难以在线监测的情况,提出了一种在只有少子样的截尾数据时利用设备运行状态信息来对单个设备的运行可靠性进行评估的方法。在该方法中,首先从设备的振动、电流信号中提取并优选出几项退化特征量;其次针对截尾数据,采用了高斯过程机械学习法拟合预测出设备失效时的各项退化特征指标值;然后以这些特征指标值为输入,借助于分布假设、贝叶斯推理,构建了一个运行可靠性的评估模型;最后通过数控刀具的失效实验对该方法进行了验证。结果表明:预测精度可以达到3%。此结果证明了该方法的可行性和有效性。
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