Wang Baoxiang, Liao Yuhe, Ding Chuancang, Zhang Xining
Shaanxi Key Laboratory of Mechanical Product Quality Assurance and Diagnostics, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China; Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System, Xi'an Jiaotong University, Xi'an 710049, China.
State Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China.
ISA Trans. 2020 Jun;101:366-378. doi: 10.1016/j.isatra.2020.01.037. Epub 2020 Feb 3.
Early bearing fault detection is crucial to avoid catastrophic accidents. However, the repetitive defect impulses indicating bearing fault are buried in heavy background noise. In the paper, a novel periodical sparse low-rank (PSLR) matrix estimation algorithm is proposed for extracting repetitive transients from noisy signal. Concretely, periodical group sparsity and low-lank property of fault transients in time-frequency domain are first revealed, and then an optimization problem is proposed for simultaneously promoting these two properties. Meanwhile, to further highlight the sparsity of fault features, the non-convex penalty functions are incorporated into the optimization problem. Then, for solving the proposed optimization problem, an iterative algorithm is derived based on alternating direction method of multipliers (ADMM) and majorization-minimization (MM), in which the traditional soft-thresholding operation is replaced by the proposed Gini-guided fault information thresholding (FIT) scheme to enhance fault transient extraction. Finally, simulated and real signals confirm the performance of proposed PSLR in extracting defect impulses from noisy vibration signal.
早期轴承故障检测对于避免灾难性事故至关重要。然而，指示轴承故障的重复性缺陷脉冲被掩埋在强烈的背景噪声中。本文提出了一种新颖的周期性稀疏低秩（PSLR）矩阵估计算法，用于从噪声信号中提取重复性瞬态信号。具体而言，首先揭示了故障瞬态信号在时频域中的周期性组稀疏性和低秩特性，然后提出了一个优化问题以同时提升这两个特性。同时，为了进一步突出故障特征的稀疏性，将非凸惩罚函数纳入优化问题。接着，为求解所提出的优化问题，基于乘子交替方向法（ADMM）和逐次逼近最小化（MM）推导了一种迭代算法，其中传统的软阈值操作被所提出的基尼引导故障信息阈值（FIT）方案所取代，以增强故障瞬态提取能力。最后，仿真信号和实际信号证实了所提出的PSLR算法在从噪声振动信号中提取缺陷脉冲方面的性能。
