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Detection of Cracks in Rotating Shafts by Using the Combination Resonances Approach and the Approximated Entropy Algorithm

机译:组合共振法与近似熵算法相结合的旋转轴裂纹检测

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Shaft crack detection is a very serious matter and machines suspected of having a crack must be treated carefully. The importance attributed to this problem is addressed due to the serious consequences when cracks are not early detected in rotating systems. Various crack detection techniques were proposed in the last years, in which the vibration based techniques have demonstrated being efficient. However, these techniques fail for the cases in which incipient cracks are concerned. Recently, a nonlinear approach to detect cracks in rotating shafts was presented. The idea is to excite the shaft by using a harmonic force to induce combination resonances in the system. If the combination resonances appear in the vibration responses of the rotating system, the presence of cracks is confirmed. However, this methodology demonstrated being effective in detecting only deep cracks. In this context, the uniqueness of this paper relies on the possibility of detecting incipient transverse cracks in rotating shafts by associating the combination resonances approach with the so-called Approximated Entropy algorithm (ApEn algorithm). ApEn is a statistical value used to quantify irregularities in data series. Patterns and correspondences between samples of the same series are searched to detect anomalies. Considering that the combination resonances change the pattern of the shaft vibration responses, the ApEn algorithm can be used to highlight the presence of such resonances and, consequently, the detection of incipient cracks. The proposed approach was numerically evaluated by considering a horizontal rotating machine. A preliminary experimental investigation is also presented. The results demonstrated the efficiency of the conveyed methodology.
机译:轴裂纹检测是非常严重的事情,怀疑带有裂纹的机器必须小心处理。由于在旋转系统中未及早发现裂纹时会产生严重后果,因此解决了归因于此问题的重要性。近年来提出了各种裂缝检测技术,其中基于振动的技术已被证明是有效的。但是,这些技术在涉及初期裂纹的情况下失败。最近,提出了一种非线性方法来检测旋转轴中的裂纹。这个想法是通过使用谐波力在系统中引起组合共振来激励轴。如果组合共振出现在旋转系统的振动响应中,则确认存在裂纹。但是,该方法论证明仅在检测深裂缝时有效。在这种情况下,本文的独特性在于通过将组合共振方法与所谓的近似熵算法(ApEn算法)相关联来检测旋转轴中初期横向裂纹的可能性。 ApEn是用于量化数据序列中不规则性的统计值。搜索相同系列的样本之间的模式和对应关系以检测异常。考虑到组合共振会改变轴振动响应的模式,因此可以使用ApEn算法突出显示这种共振的存在,从而检测出早期裂纹。通过考虑卧式旋转机对提出的方法进行了数值评估。还提供了初步的实验研究。结果证明了所传达方法的有效性。

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