| 基于小波包变换的FED驱动电路故障诊断 |
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| 引用本文： | 林雪芬,郭太良,姚剑敏,林志贤,徐胜. 基于小波包变换的FED驱动电路故障诊断[J]. 电视技术, 2011, 35(11): 36-38,87 |
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| 作者姓名： | 林雪芬 郭太良 姚剑敏 林志贤 徐胜 |
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| 作者单位： | 福州大学物理与信息工程学院,福建福州,350002 |
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| 基金项目： | 国家“863”计划重大专项(2008AA03A313); 福建省自然科学基金项目(2010J01333); 福建省教育厅资助重点项目(JA09003) |
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| 摘 要： | 根据FED驱动电路的特性,提出了一种小波包变换和神经网络相结合的方法,并将其应用于FED的驱动电路故障诊断.首先采用小波包变换对电路输出节点的电压信号进行分解,提取各频段的能量作为故障样本输入神经网络.仿真实验证明,该方法减少了故障诊断的时间,提高了故障诊断的准确率,使准确率达到87.17％.
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| 关 键 词： | FED驱动电路 故障诊断 小波包变换 神经网络 |
Fault Diagnosis of FED Drive Circuits Based on Wavelet Packet |
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| LIN Xuefen,GUO Tailiang,YAO Jianmin,LIN Zhixian,XU Sheng. Fault Diagnosis of FED Drive Circuits Based on Wavelet Packet[J]. Ideo Engineering, 2011, 35(11): 36-38,87 |
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| Authors: | LIN Xuefen GUO Tailiang YAO Jianmin LIN Zhixian XU Sheng |
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| Affiliation: | LIN Xuefen,GUO Tailiang,YAO Jianmin,LIN Zhixian,XU Sheng(College of Physics and Information Engineering,Fuhzou University,Fuzhou 350002,China) |
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| Abstract: | Based on the characteristics of FED,a fault diagnose method is proposed based on neural network and wavelet packet transformation,and is applied to FED drive circuit.Firstly,the wavelet packet is used to decompose the voltage signal of output node.The energy feature is extracted as the diagnosis sample to input into neural network.Experimentation indicates that the method can decrease fault diagnosis time and enhance the rate of accuracy to 87.17%. |
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| Keywords: | FED drive circuit fault diagnosis wavelet packet neural networks |
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