基于SNST的柱塞泵转速信号故障程度识别方法

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振动与冲击 ›› 2025, Vol. 44 ›› Issue (15) : 192-200.

故障诊断分析

基于SNST的柱塞泵转速信号故障程度识别方法

刘佳敏*1,2，周新涛1,2，吴玉文1,2，李翊宁1,2，孟帅3

作者信息 +

Plunger pump fault degree identification method based on variable rotating speed signal after SNST

LIU Jiamin*1,2, ZHOU Xintao1,2, WU Yuwen1,2, LI Yining1,2, MENG Shuai3

Author information +

文章历史 +

摘要

液压设备在运行过程中伴随着多域间的能量转换，尤其在变工况下呈现出非平稳性及非线性等特征，为状态监测与故障诊断带来难度。为了提高非平稳工况轴向柱塞泵故障诊断的性能，该研究提出采用既是运行参数又是状态参量的瞬时转速信号作为轴向柱塞泵故障诊断的信息源。通过理论分析得出瞬时转速信号的波动成分中蕴含着元件健康状态信息。提出采用同步提取标准S变换（synchro-extracting of normal S transform，SNST）对其进行线通滤波处理。利用K-medoids方法将滤波重构后的瞬时转速波动信号角度域特征值进行聚类分析，并在机电液一体化平台上进行了变转速和变负载工况试验，实现了轴向柱塞泵配流盘在正常、轻微、严重磨损时的故障诊断。研究成果可为液压设备的运行状态监测与故障诊断提供新的方法。

Abstract

Hydraulic equipment undergoes multi-domain energy conversion during operation. Especially under variable operating conditions, this process typically exhibits non-linearity and non-stationarity, which poses challenges for condition monitoring and fault diagnosis. The study introduces the utilization of the instantaneous speed (IS) signal for fault diagnosis of axial piston pumps. The IS serves both as a system dynamics parameter and a condition monitoring variable, offering significant advantages when the pump operates under non-stationary conditions. Through theoretical analysis, it has been concluded that the fluctuation components of the IS signal contain information about the health status of pumps. The synchro-extracting normal S transform (SNST) is proposed for performing line-pass filtering on the signal. The K-medoids method is then applied to cluster the angular eigenvalues of the filtered and reconstructed IS fluctuation signals. Experiments under variable speed and load conditions were conducted on an integrated mechatronic-hydraulic platform, successfully diagnosing faults in the axial piston pump's swashplate under normal, slight wear, and severe wear conditions. The research findings provide new methodologies for monitoring the operating status and diagnosing faults in hydraulic equipment.

导出引用

刘佳敏1, 2, 周新涛1, 2, 吴玉文1, 2, 李翊宁1, 2, 孟帅3. 基于SNST的柱塞泵转速信号故障程度识别方法[J]. 振动与冲击, 2025, 44(15): 192-200

LIU Jiamin1, 2, ZHOU Xintao1, 2, WU Yuwen1, 2, LI Yining1, 2, MENG Shuai3. Plunger pump fault degree identification method based on variable rotating speed signal after SNST[J]. Journal of Vibration and Shock, 2025, 44(15): 192-200

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