School of Civil Aviation, Northwestern Polytechnical University, 710072 Xi'an, China.
COMAC Flight Test Center, 201207 Shanghai, China.
ISA Trans. 2023 May;136:483-502. doi: 10.1016/j.isatra.2022.10.022. Epub 2022 Oct 26.
Faulty impulses from incipient damaged bearings are typically submerged in harmonics, random shocks, and noise, making incipient fault diagnosis challenging. The prerequisite to this problem is the robust estimation of faulty impulses; thus, this paper proposes a multiband weights-induced periodic sparse representation (MwPSR) method. Firstly, a multiband weighted generalized minimax-concave induced sparse representation (MwGSR) approach is presented to accelerate the sparse approximation process and eliminate the interference components. A new indicator, coined the frequency-weighted energy operator spectrum's kurtosis-to-entropy ratio, is defined to construct the MwGSR's weights to accentuate faulty impulses. Secondly, to enhance the periodicity of the estimated impulses, a fault period decision strategy with an improved periodic target vector is developed and embedded into MwGSR to form MwPSR eventually. Detailed simulations and experiments demonstrate that MwPSR can achieve periodic sparsity with high accuracy and robustness and is reliable for incipient bearing fault diagnosis.
初期损坏轴承产生的故障脉冲通常会淹没在谐波、随机冲击和噪声中，这使得初期故障诊断具有挑战性。这个问题的前提是对故障脉冲进行稳健估计；因此，本文提出了一种多频带加权周期稀疏表示（MwPSR）方法。首先，提出了一种多频带加权广义最小最大凹诱导稀疏表示（MwGSR）方法，以加速稀疏逼近过程并消除干扰分量。定义了一个新的指标，称为频率加权能量算子谱的峰度-摘比，用于构建 MwGSR 的权重，以突出故障脉冲。其次，为了增强估计脉冲的周期性，开发了一种具有改进周期性目标向量的故障周期决策策略，并将其嵌入到 MwGSR 中，最终形成 MwPSR。详细的仿真和实验表明，MwPSR 可以实现高精度和鲁棒性的周期性稀疏表示，并且可靠用于初期轴承故障诊断。
