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通过对变步长LMS自适应滤波算法和提升小波变换理论进行研究,将两种算法换相结合,提出一种新的提升小波变步长LMS自适应滤波改进算法;根据信号特征对更新算子和预测算子自适应的构造,对正交分解的信号进行变步长LMS自适应消噪,提高了收敛速度和稳定性;通过仿真分析,证明了改进的提升小波变步长LMS滤波算法具有较快的收敛速度和更强的抑噪能力;最后,将提出的方法应用于低速重载齿轮箱的故障诊断中,分析结果表明,该方法是一种非常有效的故障特征处理方法。
Through the research on variable-step LMS adaptive filtering algorithm and lifting wavelet transform theory, the two algorithms are combined by commutation, and a new improved LMS adaptive filtering improved algorithm is proposed. Based on the signal characteristics, the update operator And predictive operator adaptive structure, the signal of orthogonally decomposed is adaptively de-noised with variable step size LMS to improve the convergence speed and stability. The simulation analysis shows that the improved LMS filtering algorithm with variable step size has the advantages of Faster convergence speed and stronger noise suppression ability. Finally, the proposed method is applied to the fault diagnosis of low speed and heavy load gearboxes. The analysis results show that the proposed method is a very effective fault feature processing method.