Blind Source Separation of Gearbox Fault Signals under Impulse Noise

Yu Xiangmei, S. Tong
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Abstract

Aiming at the shortage of blind source separation (BSS) in processing gearbox fault signals under α stable distribution impulse noise, a new BSS algorithm based on fractional lower order (FLO) S time-frequency distribution was proposed in this paper. In this algorithm fault signals of gearbox were prewhitened in FLO subspace, then S time frequency transform for prewhitened lower-order signals were performed, finally the source signals were restored via joint approximate diagonalization. Simulation results show that the proposed algorithm can effectively restrain impulse noise influence, the BSS effect is good and robust.
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脉冲噪声下齿轮箱故障信号的盲源分离
针对α稳定分布脉冲噪声下齿轮箱故障信号盲源分离(BSS)处理的不足,提出了一种基于分数阶低阶时频分布的盲源分离算法。该算法首先在FLO子空间中对齿轮箱故障信号进行预白,然后对预白后的低阶信号进行S时频变换,最后通过联合近似对角化对源信号进行恢复。仿真结果表明,该算法能有效抑制脉冲噪声的影响,BSS效果良好,鲁棒性好。
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