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Order Spectrum Analysis for Bearing Fault Detection via Joint Application of Synchrosqueezing Transform and Multiscale Chirplet Path Pursuit

机译:通过联合应用同步应用变换和多尺度啁啾路径追踪的轴承故障检测顺序分析

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摘要

Order tracking has become one of the most effective methods for fault detection of rotating machinery under the time-varying shaft speed conditions. The transient phase estimation is very important for order tracking, especially when the tachometer installation is not convenient. The transient phase is usually obtained by integrating the instantaneous frequency (IF), so the IF estimation has attracted a great deal of concerns. This article describes a new IF estimation method based on the joint application of the synchrosqueezing transform (SST) and the multiscale chirplet path pursuit (MSCPP) method. The SST method as its high frequency resolution merits is used to estimate the frequency parameters for the parameter settings of the MSCPP method, that will resolve the high computation problem of the MSCPP method to a certain degree, so as to extensively use the high accuracy of the MSCPP method in IF estimation. The order spectrum based on the estimated IF can provide the demodulation information for the bearing fault diagnosis. The performance of the proposed method has been validated by both simulation and experimental data.
机译:订购跟踪已成为在时变轴速度条件下旋转机械故障检测最有效的方法之一。瞬态相位估计对于订单跟踪非常重要,特别是当转速计安装不方便时。瞬态阶段通常通过积分瞬时频率(IF)而获得,因此如果估计引起了很多问题。本文介绍了一种基于SynchroSquezing变换(SST)和MultiScale Chirplet路径追踪(MSCPP)方法的联合应用的新IF估计方法。作为其高频分辨率的SST方法用于估计MSCPP方法的参数设置的频率参数,这将在一定程度上解析MSCPP方法的高计算问题,以便广泛地使用高精度如果估计的IFSCPP方法。基于估计的订单频谱如果可以为轴承故障诊断提供解调信息。通过模拟和实验数据验证了所提出的方法的性能。

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