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Control of phases by ESPRIT and WLSE methods for the early detection of gear cracks

机译:通过ESPRIT和WLSE方法进行相位控制以及早发现齿轮裂纹

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The early detection of gear faults remains a major problem, especially when the gears are subjected to non stationary phenomena due to defects. In industrial applications, the crack of tooth is a default very difficult to detect whether using the time descriptors or the frequency analysis. In this work and based on a numerical model, we prove that the crack default affects directly the phase of the frequency component of the defective wheel (frequency modulation). To properly estimate the phases, we suggest two high-resolution techniques (Estimation of Signal Parameters via Rotational Invariance Techniques ESPRIT with a sliding window and Weighted Least Squares Estimator WLSE). The results of both methods are compared to the phase obtained by Hilbert transform. The three techniques are then applied on a multiplicative signal with a frequency modulation to show the influence of the amplitude modulation on the quality of phase estimation. We note that the ESPRIT method is much better in the estimation of frequencies while WLSE shows much efficiency in the estimation of phases if we keep the frequencies almost stables.
机译:齿轮故障的早期检测仍然是一个主要问题,尤其是当齿轮由于缺陷而遭受非平稳现象的时候。在工业应用中,默认情况下很难使用时间描述符或频率分析来检测牙齿的裂纹。在这项工作中,并基于一个数值模型,我们证明了裂纹缺损会直接影响缺陷车轮的频率分量的相位(频率调制)。为了正确估计相位,我们建议使用两种高分辨率技术(通过带有滑动窗口和加权最小二乘估计器WLSE的旋转不变技术ESPRIT估计信号参数)。将两种方法的结果与通过希尔伯特变换获得的相位进行比较。然后将这三种技术应用于具有频率调制的乘法信号,以显示幅度调制对相位估计质量的影响。我们注意到,如果我们保持频率几乎稳定,则ESPRIT方法在频率估计方面要好得多,而WLSE在相位估计方面显示出很大的效率。

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