揭震国, 王细洋. 齿轮故障诊断的时域同步平均改进算法[J]. 失效分析与预防, 2020, 15(5): 292-296. DOI: 10.3969/j.issn.1673-6214.2020.05.004
    引用本文: 揭震国, 王细洋. 齿轮故障诊断的时域同步平均改进算法[J]. 失效分析与预防, 2020, 15(5): 292-296. DOI: 10.3969/j.issn.1673-6214.2020.05.004
    JIE Zhen-guo, WANG Xi-yang. Time Domain Synchronization Average Improved Algorithm for Gear Fault Diagnosis[J]. Failure Analysis and Prevention, 2020, 15(5): 292-296. DOI: 10.3969/j.issn.1673-6214.2020.05.004
    Citation: JIE Zhen-guo, WANG Xi-yang. Time Domain Synchronization Average Improved Algorithm for Gear Fault Diagnosis[J]. Failure Analysis and Prevention, 2020, 15(5): 292-296. DOI: 10.3969/j.issn.1673-6214.2020.05.004

    齿轮故障诊断的时域同步平均改进算法

    Time Domain Synchronization Average Improved Algorithm for Gear Fault Diagnosis

    • 摘要: 针对经典数据重采样算法实现时域同步平均的频率跟踪时存在重建误差大、计算速度慢的问题,提出一种三次样条重采样实现频率跟踪的算法。该算法首先采用峰值搜索算法搜集时标信号,然后以得到的时标信号分割数据形成多个数据段,最后采用三次样条函数重采样各数据段。试验结果表明:改进算法所需的计算资源从平方阶减至线性阶,抑制了噪声和非感兴趣频率,提高约10%的齿轮故障特征频率的提取效果。

       

      Abstract: Aiming at reconstruction error and slow calculation speed in the frequency tracking of time domain synchronous average, an improved TSA based on three spline resampling is proposed in this study. Firstly, the algorithm uses the peak search algorithm to collect time-scale signals, secondly, the data are divided into multiple data segments using the obtained time-scale signals, and finally a cubic spline function is used to resample each data segment. Experimental results show that the computational resources required for the proposed algorithm are reduced from the square level to the linear level. The proposed algorithm suppresses noise and uninteresting frequencies, and the performance of fault feature extraction increases 10% compared with that of the conventional one.

       

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