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基于虚拟仪器技术和神经网络的电晕辐射场监测系统设计

DOI: 10.13336/j.1003-6520.hve.2015.01.047, PP. 333-338

Keywords: 电晕放电,火花放电,虚拟仪器,神经网络,模式识别

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Abstract:

为了实现电晕放电辐射信号的自动化监测与识别,以PXIe-5185数字化仪为主要硬件,采用虚拟仪器技术和神经网络算法研制了电晕放电辐射信号监测与识别系统。该系统模仿示波器设计操控界面,具有信号采集、数据处理、频域分析、数据存储、报告生成等功能。系统综合采用触发电平限制、数字滤波和神经网络识别3种于信号处理,可有效降低数据存储压力。试验结果表明,BP神经网络可有效识别与区分电晕放电和火花放电,在改变电极、增加电晕放电样本复杂性的情况下,对电晕放电的识别率仍然可达87%。监测系统为进一步研究电晕放电信号的特性奠定了基础,其信号处理流程可推广应用于其他脉冲信号监测领域。

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