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Automatic localization of the rotor-stator rubbing fault based on acoustic emission method and higher-order statistics

机译:基于声发射法和高阶统计的转子定子摩擦故障自动定位

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Localization to the rotor-stator rubbing fault of rotating machinery such as aero-engines has been attracting plenty of attentions in fault diagnosis field. Present study attempts to effectively and accurately localize such rubbing sources based on modal AE method automatically. In order to explore the propagation characteristic of rubbing signals, theoretical analysis and finite element simulation on a stator case are conducted. And the dependence of accuracy of time difference of arrival (TDOA) method on the propagation characteristic is investigated. Based on the analysis result, a higher-order statistics (HOS) algorithm is introduced into acoustic emission (AE) to automatically identify the arrival time of rubbing signals and localize the rubbing source via automatic threshold selection. To verify the effectiveness of the proposed AE method to recognize the rubbing fault, a series of rubbing tests are carried out. It is demonstrated by the experimental results that the accuracy of the proposed method is improved compared with conventional TDOA methods since more than half of the sources localized at the rubbing region can be identified in almost all cases and the identification accuracy is up to 80 % at threshold of 85 % of amplitude.
机译:转子定位的定位旋转机械如空气发动机的旋转机械的故障一直在出现故障诊断领域的大量关注。目前的研究试图基于自动模态AE方法有效准确地定位了这种摩擦源。为了探索摩擦信号的传播特性,进行定子壳体上的理论分析和有限元模拟。研究了到达时间差的准确度(TDOA)方法对传播特性的依赖性。基于分析结果,将高阶统计(HOS)算法引入声发射(AE)中,以自动识别摩擦信号的到达时间并通过自动阈值选择本地化摩擦源。为了验证所提出的AE方法识别摩擦故障的有效性,进行了一系列摩擦测试。通过实验结果证明了所提出的方法的准确性与传统的TDOA方法得到改善,因为在几乎所有情况下可以在几乎所有情况下识别摩擦区域的源的超过一半源,并且识别精度高达80%幅度为85%的幅度。

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