中文摘要：

在操作潜在的适用的差错监视具有到高速度火车的安全操作的批评重要性。主要挑战之一是怎么把相关信号区分开来到轴承的运作的条件与从包围环境射出的噪音。在这个工作，我们为分析从为由通过一个多尺度的形态学分析过程检验他们的词法模式光谱(MPS ) 忍受健康条件的诊断卷轴承收集的声学的排放信号报导一个过程。声学的排放信号源于适用的一种给定的类型的结果表演指责相当类似的 MPS 弄弯的份额。以样品，熵和 MPS 的 Lempel-Ziv 复杂性弄弯的进一步的考试建议这二个参数能被利用决定损坏模式。

英文摘要：

Monitoring of potential bearing faults in operation is of critical importance to safe operation of high speed trains.One of the major challenges is how to differentiate relevant signals to operational conditions of bearings from noises emitted from the surrounding environment.In this work,we report a procedure for analyzing acoustic emission signals collected from rolling bearings for diagnosis of bearing health conditions by examining their morphological pattern spectrum（MPS） through a multi-scale morphology analysis procedure.The results show that acoustic emission signals resulted from a given type of bearing faults share rather similar MPS curves.Further examinations in terms of sample entropy and Lempel-Ziv complexity of MPS curves suggest that these two parameters can be utilized to determine damage modes.