Where next for condition monitoring of rotating machinery
Where next for condition monitoring of rotating machinery
复制标题
旋转机械状态监测的下一步
DOI：
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复制
发表时间：
2006
期刊：
影响因子：
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通讯作者：
M. Friswell
中科院分区：
文献类型：
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作者：
A. Lees;M. Friswell
多年来，随着数据分析算法的显著但相当渐进的改进，状态监测已经取得了进展。旋转机械状态监测的模式识别方法已经比较成熟，能够成功地对多种类型的故障进行检测和分类。然而，有些故障很难区分，故障定位需要机器的空间模型。要有用，这些模型必须是机器的准确表示。当然，与任何模型一样，所需的精度取决于模型的用途。本文考虑了各种故障和机器的模型，强调了估计方法的使用，并讨论了所需的模型保真度。给出了裂缝、不平衡、弯曲、错位等断层的实例。考虑到可能建立的关于运行机器的信息，以及如何在未来的状态监测系统中实施这些信息以显著提高其价值。
Condition monitoring has progressed for many years with significant but fairly incremental improvements to algorithms for data analysis. Pattern recognition methods for the condition monitoring of rotating machinery are well established and can successfully detect and classify many types of faults. However, some faults are difficult to distinguish and locating faults requires a spatial model of the machine. To be useful, these models must be an accurate representation of the machine. Of course, as with any model, the required accuracy depends on the use to which the model is put. This paper considers models of various faults and machines, highlights the use of estimation methods, and discusses the required model fidelity. Examples of faults such as cracks, unbalance, bends and misalignment are given. Consideration is given to the information that may be established about an operational machine, and how it might be implemented in future condition monitoring systems to significantly enhance their value.