Although the envelope-spectrum-based methods for bearing fault diagnosis have been widespread in the scientific community, their application to autonomous diagnosis is hindered by the specified selection of informative frequency bands and the threshold calculation. This article, therefore, proposes a novel autonomous diagnosis method via fault-induced envelope spectrum (FIES) and moving peaks-over-threshold (MPOT) approach. A fault-induced filter is first designed to reveal all the informative bands of the spectral coherence (SCoh) rather than only a specified band. Then, the FIES is used to extract each fault signature, which weights and integrates along the spectral frequency axis of the SCoh. Subsequently, the MPOT is proposed to calculate a frequency-dependent threshold for the FIES, which not only concentrates the heavy-tailed statistical characteristics of faults but also removes the influence of the nonstationary statistical characteristics for the threshold. Finally, the healthy indicator and suspected fault indicator are compared with warn users of the possible risks, meanwhile, making a decision for autonomous diagnosis. The effectiveness of the proposed method is verified by the experimental data. Results are found superior to two existing envelope-spectrum-based methods, which are more practical in terms of autonomous fault diagnosis and health monitoring.

中文翻译：

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基于故障诱发包络谱和超阈值移动峰值法的自主轴承故障诊断

尽管基于包络谱的轴承故障诊断方法已在科学界广泛应用，但其在自主诊断中的应用受到信息频段的指定选择和阈值计算的阻碍。因此，本文提出了一种通过故障引起包络谱（FIES）和移动峰值阈值（MPOT）方法的新型自主诊断方法。故障诱发滤波器首先被设计为揭示光谱相干性 (SCoh) 的所有信息波段，而不是仅显示指定波段。然后，FIES 用于提取每个故障特征，并沿 SCoh 的频谱频率轴进行加权和积分。随后，提出MPOT来计算FIES的频率相关阈值，该阈值不仅集中了故障的重尾统计特征，而且消除了非平稳统计特征对阈值的影响。最后将健康指标与疑似故障指标进行比较，警告用户可能存在的风险，同时做出自主诊断决策。实验数据验证了所提方法的有效性。结果发现优于两种现有的基于包络谱的方法，这在自主故障诊断和健康监测方面更实用。