Time‐varying fault impulse amplitude and time‐varying fault impulse interval are the main challenges for rolling bearing fault diagnosis under variable speed conditions. In this paper, a vibration‐based rolling bearing fault characteristic frequency (FCF) estimation and novel diagnosis method under time‐varying rotational speeds are proposed, using the demodulation transform. First, the FCFs with weak amplitudes are estimated, using the optimization‐based demodulation transform, whose main concept is that with the optimal demodulation operator (DO), the time‐varying frequency component can be transformed into a constant one and the largest peak can be detected in the spectrum of the demodulated signal. Second, the rolling bearing is successfully diagnosed with hypothesis‐based demodulation transform, whose main concept is that the rotational frequency (RF)‐related DOs under different fault types are estimated, based on the estimated FCFs and the fault characteristic coefficients (FCCs). Then the RF‐related peak in the spectrum of the demodulated signal can be used to detect rolling bearing fault. The effectiveness of the proposed method is verified, using both simulated signal and measured vibration signal. Novel comparisons with the current methods demonstrate much better ability of the proposed method for diagnosis of rolling bearing under variable speed conditions.

中文翻译：

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新型解调技术监测变速条件下滚动轴承的振动健康

时变故障脉冲幅度和时变故障脉冲间隔是变速条件下滚动轴承故障诊断的主要挑战。本文提出了一种基于时变转速的基于振动的滚动轴承故障特征频率（FCF）估计方法和新的诊断方法。首先，使用基于优化的解调变换来估计幅度较弱的FCF，其主要概念是使用最佳解调算子（DO），可以将时变频率分量变换为一个常数，最大峰值可以在解调信号的频谱中被检测到。其次，通过基于假设的解调变换成功诊断了滚动轴承，其主要概念是根据估算的FCF和故障特征系数（FCC）估算不同故障类型下与旋转频率（RF）相关的DO。然后，解调信号频谱中与RF相关的峰值可用于检测滚动轴承故障。利用仿真信号和实测振动信号验证了所提方法的有效性。与当前方法的新颖比较表明，该方法在变速条件下诊断滚动轴承的能力要好得多。利用仿真信号和实测振动信号验证了所提方法的有效性。与当前方法的新颖比较表明，该方法在变速条件下诊断滚动轴承的能力要好得多。利用仿真信号和实测振动信号验证了所提方法的有效性。与当前方法的新颖比较表明，该方法在变速条件下诊断滚动轴承的能力要好得多。