Abstract:Determination of the diagnosis thresholds is crucial for the fault diagnosis of industry assets. Rotor machines under different working conditions are especially challenging because of the dynamic torque and speed. In this paper, an advanced machine learning based signal-processing innovation termed the multivariate state estimation technique is proposed to improve the accuracy of the diagnosis thresholds. A novel preprocessing technique called vibration resonance spectrometry is also applied to achieve a low … Show more
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