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Gear Wear Process Monitoring Using a Sideband Estimator Based on Modulation Signal Bispectrum

机译:使用基于调制信号双谱的边带估计器进行齿轮磨损过程监控

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As one of the most common gear failure modes, tooth wear can produce nonlinear modulation sidebands in the vibration frequency spectrum. However, limited research has been reported in monitoring the gear wear based on vibration due to the lack of tools which can effectively extract the small sidebands. In order to accurately monitor gear wear progression in a timely fashion, this paper presents a gear wear condition monitoring approach based on vibration signal analysis using the modulation signal bispectrum-based sideband estimator (MSB-SE) method. The vibration signals are collected using a run-to-failure test of gearbox under an accelerated test process. MSB analysis was performed on the vibration signals to extract the sideband information. Using a combination of the peak value of MSB-SE and the coherence of MSB-SE, the overall information of gear transmission system can be obtained. Based on the amplitude of MSB-SE peaks, a dimensionless indicator is proposed to assess the effects of gear tooth wear. The results demonstrated that the proposed indicator can be used to accurately and reliably monitor gear tooth wear and evaluate the wear severity.
机译:作为最常见的齿轮故障模式之一,牙齿磨损会在振动频谱中产生非线性调制边带。但是,由于缺乏能够有效提取小边带的工具,因此基于振动来监测齿轮磨损的研究报道很少。为了及时准确地监测齿轮磨损状况,本文提出了一种基于振动信号分析的齿轮磨损状态监测方法,该方法采用基于调制信号双谱的边带估计器(MSB-SE)方法。振动信号是在加速测试过程中使用齿轮箱从运行到失败的测试来收集的。对振动信号进行MSB分析以提取边带信息。通过结合MSB-SE的峰值和MSB-SE的相干性,可以获得齿轮传动系统的整体信息。基于MSB-SE峰值的幅度,提出了无量纲指示器来评估齿轮磨损的影响。结果表明,所提出的指标可用于准确可靠地监测齿轮齿磨损并评估磨损严重程度。

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