根据强噪声干扰环境下齿轮箱故障非平稳信号是由持续振荡成分(高共振成分)和非持续振荡的瞬态成分(低共振成分)混合而成,且其各成分存在频率重叠而不能利用传统的基于频率不同的方法对其进行有效处理的特点,提出了构造复合Q因子基(高Q因子基及低Q因子基)对故障信号进行处理的方法,对提取齿轮箱各故障的冲击性信号特征取得了良好的效果.仿真信号分析及应用实例分析结果表明了算法的可行性及有效性,为强噪声干扰环境下的机械故障信号提取提供了一种方法.
As the gear-box non-stationary fault information submerged in strong noise environment is a mixture of sustained oscillations and non-oscillatory transients, which are frequency-overlapped and cannot be processed effectively based on frequency, this paper proposes a method that constructs composite Q-factor bases ( high-Q factor base and low-Q factor base) adaptively to process the fault signal, and a favorable effect was achieved in the extraction of the impulse signal characteristics of gear-box faults. The analysis result of simulation data and application examples confirm the feasibility and validity of this method, which provides a separation of mechanical fault signals in strong noise environment.