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Motor current signature analysis for gearbox condition monitoring under transient speeds using wavelet analysis and dual-level time synchronous averaging

机译:利用小波分析和双级时间同步平均技术在瞬态转速下监控变速箱状态的电动机电流信号分析

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This paper focuses on analyzing motor current signature for fault diagnosis of gearboxes operating under transient speed regimes. Two different strategies are evaluated, extensively tested and compared to analyze the motor current signature in order to implement a condition monitoring system for gearboxes in industrial machinery. A specially designed test bench is used, thoroughly monitored to fully characterize the experiments, in which gears in different health status are tested. The measured signals are analyzed using discrete wavelet decomposition, in different decomposition levels using a range of mother wavelets. Moreover, a dual-level time synchronous averaging analysis is performed on the same signal to compare the performance of the two methods. From both analyses, the relevant features of the signals are extracted and cataloged using a self-organizing map, which allows for an easy detection and classification of the diverse health states of the gears. The results demonstrate the effectiveness of both methods for diagnosing gearbox faults. A slightly better performance was observed for dual-level time synchronous averaging method. Based on the obtained results, the proposed methods can used as effective and reliable condition monitoring procedures for gearbox condition monitoring using only motor current signature.
机译:本文着重分析电动机电流信号,以对瞬态转速下运行的变速箱进行故障诊断。对两种不同的策略进行了评估,广泛测试并进行了比较,以分析电动机电流信号,以便为工业机械中的变速箱实施状态监控系统。使用专门设计的测试台,对其进行全面监控,以全面表征实验,在其中测试处于不同健康状态的齿轮。使用离散小波分解分析测量的信号,并使用一系列母小波以不同的分解级别进行分析。此外,对同一信号执行了双级时间同步平均分析,以比较两种方法的性能。从这两种分析中,信号的相关特征都可以使用自组织图提取和分类,从而可以轻松检测和分类齿轮的各种健康状态。结果表明,这两种方法都可用于诊断齿轮箱故障。双层时间同步平均方法的性能稍好一些。基于获得的结果,所提出的方法可以用作仅使用电动机电流签名的变速箱状态监测的有效且可靠的状态监测程序。

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