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AdSR Based Fault Diagnosis for Three-Axis Boring and Milling Machine

机译:基于AdSR的三轴镗铣床故障诊断。

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This paper introduced an adaptive stochastic resonance (AdSR) signal processing technique to extract fault feature of machining accuracy decay in boring and milling machine providing a vibration time-frequency distribution with adaptable precision. The AdSR uses a correlation coefficient of the input signals and noise as a weight to construct the weighted kurtosis (WK) index. The influence of high frequency noise is alleviated and the index used in traditional SR is improved accordingly. The AdSR with WK can obtain optimal parameters adaptively. In addition, through the secondary utilization of noise, AdSR makes the signal output waveform smoother and the fluctuation period more obvious. It has been found that AdSR appears to be a better tool compared to fast Fourier transform for fault characterization extraction in boring and milling machine in experiment case. It has been concluded that AdSR based signal processing technology successfully diagnosis the fault of machining accuracy decay in three-axis boring and milling machine.
机译:本文介绍了一种自适应随机共振(AdSR)信号处理技术,以提取镗铣床中加工精度下降的故障特征,从而提供具有合适精度的振动时频分布。 AdSR使用输入信号和噪声的相关系数作为权重来构建加权峰度(WK)指数。减轻了高频噪声的影响,从而改善了传统SR中使用的指标。具有WK的AdSR可以自适应地获取最佳参数。另外,通过二次利用噪声,AdSR使信号输出波形更平滑,波动周期更加明显。已经发现,与快速傅里叶变换相比,AdSR似乎是一种更好的工具,用于在实验情况下在镗铣床中进行故障特征提取。结论是,基于AdSR的信号处理技术成功地诊断了三轴镗铣床加工精度下降的故障。

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