The (pseudo-) cyclostationarity-based spectral analysis tools can be generated by arithmetic averaging or weighted averaging of spectral correlation/coherence for rotating machinery fault diagnosis. However, conventional arithmetic or weighted averaging can hardly adequately eliminate broadband interfering noise under harsh operating conditions, thus compromising fault diagnosis capability. To address this problem, motivated by the properties of the convolution theorem, a new cyclic spectral analysis tool called (pseudo-) cyclostationarity-based product envelope spectrum is developed via the product of multiple spectral frequency components of spectral correlation/coherence (each spectral frequency component can be regarded as a special envelope spectrum containing certain useful information). A generalized construction framework is established and a specific construction methodology is proposed, which incorporates a novel estimation and discrimination approach of frequency domain fault information distribution. The frequency domain product enables the proposed method to both adaptively extract fault features distributed in multiple frequency bands and effectively eliminate interference from in-band and noise-dominated frequency bands. The performance of the developed approach is verified using simulation signals, experimental signals of different railway axle-box bearing faults and a field test signal of rolling element fault of railway locomotive axle-box bearing and finally by comparison with state-of-the-art methods. The results demonstrate that the proposed method has the capability to reduce acyclic-stationary noise and enhance (pseudo-) cyclostationary components, and thus is capable of effectively diagnosing different faults of railway axle-box bearings.

中文翻译：

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从频谱相关性/相干性生成的产品包络频谱，用于铁路轴箱轴承故障诊断


基于（伪）环平稳性的频谱分析工具可以通过频谱相关性/相干性的算术平均或加权平均来生成，用于旋转机械故障诊断。然而，传统的算术或加权平均法在恶劣的工作条件下几乎无法充分消除宽带干扰噪声，从而影响了故障诊断能力。为了解决这个问题，在卷积定理特性的推动下，通过频谱相关性/相干性的多个频谱频率分量的乘积（每个频谱频率分量可以被视为包含某些有用信息的特殊包络频谱），开发了一种新的循环频谱分析工具，称为（伪）基于环平稳性的乘积包络频谱。建立了广义的构造框架，提出了一种具体的构造方法，该方法结合了一种新颖的频域故障信息分布估计和判别方法。频域积使所提方法既能自适应地提取分布在多个频段的故障特征，又能有效消除带内和噪声主导频段的干扰。利用仿真信号、不同铁路轴箱轴承故障的实验信号和铁路机车轴箱轴承滚动体故障的现场试验信号，验证了所提方法的性能，最后与现有方法进行了对比。结果表明，所提方法具有降低非循环稳态噪声和增强（伪）循环平稳分量的能力，因此能够有效诊断铁路轴箱轴承的不同故障。