This study investigates the potential to improve the fault detection capability of sparsity-based blind filtering. It optimizes a finite impulse response filter to maximize the sparsity of the squared envelope spectrum (SES) of vibration signals. However, the method is to be highly prone to fail optimization due to the immense number of non-fault-related second-order cyclostationary interferences. These interferences can skew the sparsity estimation of the SES and thus impair the sparsity-based blind filtering method. Even whitening or signal separation methods can fail to remove such cyclostationary components adequately. Hence, the technique is unlikely to function particularly on the signals measured on complex industrial machines. This paper extends the initial study introducing sparsity-based blind filtering in the literature. It proposes refining the filter optimization’s objective function by targeting narrow frequency bandwidths on the SES to avoid non-fault-related peaks. The narrow bandwidths are selected by exploiting the available engineering knowledge, such as an average shaft speed. The proof of concept is shown on simulated signals, and the performance tests are made on signals measured on an industrial rotating machine and a wind turbine gearbox. The study’s outcome demonstrates that targeting automatically selected narrow bandwidths bounded by shaft speed harmonics can significantly improve the detection capability of sparsity-based blind filtering.

本研究调查了提高基于稀疏性的盲过滤的故障检测能力的潜力。它优化了有限脉冲响应滤波器，以最大化振动信号的平方包络谱 (SES) 的稀疏性。然而，由于大量非故障相关的二阶循环平稳干扰，该方法很容易优化失败。这些干扰会扭曲 SES 的稀疏性估计，从而削弱基于稀疏性的盲过滤方法。即使是白化或信号分离方法也无法充分去除此类循环平稳成分。因此，该技术不太可能特别适用于在复杂工业机器上测量的信号。本文扩展了文献中引入基于稀疏性的盲过滤的初步研究。它建议通过针对 SES 上的窄频率带宽来改进滤波器优化的目标函数，以避免非故障相关的峰值。窄带宽是通过利用可用的工程知识（例如平均轴速度）来选择的。概念验证显示在模拟信号上，性能测试是根据在工业旋转机器和风力涡轮机齿轮箱上测量的信号进行的。该研究的结果表明，以轴速谐波为界的自动选择的窄带宽为目标可以显着提高基于稀疏性的盲过滤的检测能力。窄带宽是通过利用可用的工程知识（例如平均轴速度）来选择的。概念验证显示在模拟信号上，性能测试是根据在工业旋转机器和风力涡轮机齿轮箱上测量的信号进行的。该研究的结果表明，以轴速谐波为界的自动选择的窄带宽为目标可以显着提高基于稀疏性的盲过滤的检测能力。窄带宽是通过利用可用的工程知识（例如平均轴速度）来选择的。概念验证显示在模拟信号上，性能测试是根据在工业旋转机器和风力涡轮机齿轮箱上测量的信号进行的。该研究的结果表明，以轴速谐波为界的自动选择的窄带宽为目标可以显着提高基于稀疏性的盲过滤的检测能力。