基于粒子滤波和自回归谱的液压泵故障诊断

Fault diagnosis of hydraulic pump based on particle filtering and autoregressive spectrum

针对飞机轴向柱塞式液压泵的工作状态监控问题,提出了一种基于液压泵振动信号分析处理的故障诊断新方法。通过对加速度传感器的原始数据序列进行信号建模,利用粒子数优化后的粒子滤波算法进行降噪;根据滤波后信号的自回归谱提取特征值,结合液压泵的故障机理分析其工作状态,实现对液压泵的故障分析和诊断。实验及仿真结果表明,粒子滤波可有效跟随原始信号并滤除噪声干扰,基于粒子滤波和自回归谱的液压泵故障诊断方法能有效地提取故障特征值,实现故障诊断和识别。

Aiming at the monitoring problem of running state of axial plunger pump used on some airplanes,a new fault diagnostic method based on analyzing and processing the vibration signals of hydraulic pump shell was presented.Through modeling the original data sequence obtained with accelerometers,using optimized particle filtering to reduce noise,extracting the eigenvalue of the autoregressive spectral of the filtered signals and analyzing the working conditions of the hydraulic pump according to its working principle,the fault analysis and diagnosis of hydraulic pump are achieved.The study shows that particle filtering can effectively follow the original signal and filter out noise jamming;and the proposed fault diagnosis method can effectively extract the fault characteristic value and achieve fault diagnosis and identification.