液压泵是液压系统的心脏，其故障诊断是液压系统故障诊断的重要部分。由于流体的压缩性、泵源与伺服系统的流固耦合作用及液压泵本身具有大幅度的固有机械振动，使得液压泵的故障机理复杂，故障特征提取困难，故障诊断的模糊性强。大量的液压泵故障诊断数据表明，通过泵源出口检测到的故障信号常**扰信号淹没，单一故障检测信号常呈现出强的模糊性，采用常规的信号处理方法难以提升有效的故障特征。

从故障诊断学的角度来看，任何一种诊断信息都是模糊的，对任何一种诊断对象，用单一信息来反映其状态行为都是不完整的，如果从多方面获取同一对象的多维故障冗余信息加以综合利用，就能对系统进行更可靠更的监测和诊断。本文针对柱塞泵球头松动故障模式，通过在液压泵出口配置振动传感器和压力传感器进行故障检测，通过小波分析进行信号消噪处理，利用主成分分析提取有效融合信息，采用改进算法的BP神经网络实现液压泵微弱信号或多故障的有效诊断。

A10VO100DRG/31R-PWA12NOO,A10VO140DRG/31R-PWA12NOO,柱塞泵A10VO18DR/31R-PWA12NOO,A10VO28DR/31R-PWA12NOO,柱塞泵A10VO45DR/31R-PWA12NOO,A10VO71DR/31R-PWA12NOO,柱塞泵A10VO100DR/31R-PWA12NOO,A10VO140DR/31R-PWA12NOO,柱塞泵A10VO18DRG/31R-PPC12NOO,A10VO28DRG/31R-PPC12NOO,柱塞泵A10VO45DRG/31R-PPC12NOO,A10VO71DRG/31R-PPC12NOO,柱塞泵A10VO100DRG/31R-PPC12NOO,A10VO140DRG/31R-PPC12NOO,柱塞泵A10VO18DR/31R-PPC12NOO,A10VO28DR/31R-PPC12NOO,柱塞泵A10VO45DR/31R-PPC12NOO,A10VO71DR/31R-PPC12NOO,柱塞泵A10VO100DR/31R-PPC12NOO,A10VO140DR/31R-PPC12NOO,柱塞泵A10VO18DRG/31R-PSC12NOO,A10VO28DRG/31R-PSC12NOO,柱塞泵A10VO45DRG/31R-PSC12NOO,A10VO71DRG/31R-PSC12NOO,柱塞泵A10VO100DRG/31R-PSC12NOO,A10VO140DRG/31R-PSC12NOO,柱塞泵A10VO18DR/31R-PSC12NOO,A10VO28DR/31R-PSC12NOO,柱塞泵A10VO45DR/31R-PSC12NOO,A10VO71DR/31R-PSC12NOO,柱塞泵A10VO100DR/31R-PSC12NOO,A10VO140DR/31R-PSC12NOO,柱塞泵A10VO18DRG/31R-PRC12NOO,A10VO28DRG/31R-PRC12NOO,柱塞泵A10VO45DRG/31R-PRC12NOO,A10VO71DRG/31R-PRC12NOO,柱塞泵A10VO100DRG/31R-PRC12NOO,A10VO140DRG/31R-PRC12NOO,柱塞泵A10VO18DR/31R-PRC12NOO,A10VO28DR/31R-PRC12NOO,柱塞泵A10VO45DR/31R-PRC12NOO,A10VO71DR/31R-PRC12NOO,柱塞泵A10VO100DR/31R-PRC12NOO,A10VO140DR/31R-PRC12NOO,柱塞泵A10VO18DRG/31R-PUC12NOO,A10VO28DRG/31R-PUC12NOO,柱塞泵A10VO45DRG/31R-PUC12NOO,A10VO71DRG/31R-PUC12NOO,柱塞泵A10VO100DRG/31R-PUC12NOO,A10VO140DRG/31R-PUC12NOO,柱塞泵A10VO18DR/31R-PUC12NOO,A10VO28DR/31R-PUC12NOO,柱塞泵A10VO45DR/31R-PUC12NOO,A10VO71DR/31R-PUC12NOO,柱塞泵
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