基于AR模型的Kolmogorov-Smirnov检验性能退化及预测研究

设备性能退化评估是对现有故障诊断技术的全新拓展，它为更有效地实现智能主动维护提供参考，更有利于实现设备的零停机率。开展对设备的性能退化评估研究，还可以实现对设备的性能预测维护功能，大大提高设备运行的可靠性。提出了基于AR预测白噪化的Kolmogorov-Smirnov检验方法，同时实现了滚动轴承的全寿命实验。通过对轴承全寿命实验数据的分析研究，论证了本方法在设备性能退化评估及预测中的研究价值，相对于有效值等传统方法，它不仅能够显著地表现前期的微弱退化状态，而且还能有条件地更早指示设备的异常状态，对于故障预测的研究具有较大的意义。

Performance degradation assessment by Kolmogorov-Smirnov test and prognosis based on AR model

Equipment performance degradation assessment can give effective reference to intelligent proactive maintenance to realize near-zero downtime.By carrying out the research on performance degradation assessment,the predictive maintenance for the equipment can be realized which can improve the reliability of the equipment.Kolmogorov-Smirnov test based on AR model was proposed.According to the analysis of data in rolling bearing’s whole life time(normal-fault-failure),the proposed method can effectively realize the performance degradation assessment and prognosis of the bearings.Comparing with traditional method,it can not only obviously detect incipient weak defect and indicate performance degradation process but also detect abnormal stage earlier before the start of bearing failure under some conditions.