基于BP神经网络的便携式阀门在线监测及诊断系统研究

Research on the On-Line Monitoring and Diagnostic System of Portable Valve Based on BP Neural Network

针对现场使用的阀门监测及检修装置其附件等易耗品不易购买,甚至停止供货的风险,开发了基于CRIO的嵌入式阀门诊断系统,其特点为集成度高、体积小、精度高、抗振及抗干扰能力强等特性;在大E/P两侧均加装减压阀,有效降低由于气源压力过大或气源不稳定对阀门造成的损坏;无需拆解阀门即可对阀门本体、定位器等快速定位故障及诊断阀门健康状态。

For the field use of valve monitoring and maintenance equipment,such as accessories and other consumables are not easy to buy,or even stop the risk of supply,the development of Crio-based embedded valve diagnostic system,characterized by high integration,small volume,high precision,anti-vibration and strong anti-jamming capability,etc.on the large e/p both sides are equipped with pressure reducing valve,Effectively reduce the damage caused by the valve due to excessive air pressure or instability of the gas source,the valve body,positioner and so on can be quickly located fault and diagnose the valve health condition without disassembling the valve.