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中文摘要：
摘要：紫外成像检测技术是一种检测高压设备故障的新方法；在此技术上研究设计了一种放电故障紫外检测系统，该系统能对实时采集的紫外图像进行相关的技术处理，同时可对故障点进行准确定位；根据数据建立了设备状态模型并提出一种基于人工神经网络的状态识别方法，应用MATLAB工具进行神经网络的设计和模拟，仿真结果达到预期效果；该系统可以准确地诊断设备的故障和运行状况，有较好运用前景和理论意义。t
英文摘要：
Abstract： Ultraviolet imaging technology is a new method for the fault detection of high--voltage electric equipment. Based on the tech- nology , I designed an ultraviolet detection system of discharge faulto It can deal with the real-- time collection of ultraviolet image and locate fault point. According to the data, the paper set up state model and put forward a kind of state recognition method based on artificial neural network. Then the paper carried out a neural network design and simulation with MATLAB, and achieved the expected results. The system can accurately diagnose fault and operation condition of the equipment, it has good application prospects and theoretical significance.
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