| 基于神经网络数据融合技术的诊断系统的研究 |
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| 引用本文： | 赵娟,李国昌,张玉彬,孙卫平.基于神经网络数据融合技术的诊断系统的研究[J].河北机电学院学报,2010(6):378-380. |
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| 作者姓名： | 赵娟 李国昌 张玉彬 孙卫平 |
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| 作者单位： | [1]河北科技大学信息科学与工程学院,河北石家庄050018 [2]河北科技大学经济管理学院,河北石家庄050018 |
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| 摘 要： | 神经网络数据融合技术的诊断系统是以电机振动信号和电流、电压信号为研究对象的,对采集到的3类信号进行实时处理,运用神经网络对数据进行局部诊断,再利用数据融合技术对故障信号进行全局分析融合,从而达到对电机故障类型的准确判断。通过运行表明,应用在故障诊断中的神经网络数据融合技术是一种故障识别率高、方便灵活而且诊断精度高的故障诊断方法。
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| 关 键 词： | 神经网络 数据融合 故障诊断 故障信号 |
Study on integrated fault diagnosis system based on neural network data fusion technology |
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| Authors: | ZHAO Juan LI Guo-chang ZHANG Yu-bin SUN Wei-ping |
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| Affiliation: | 1. College of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang Hebei 050018, China; 2. College of Economies and Management, Hebei University of Science and Technology, Shijiazhuang Hebei 050018, China) |
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| Abstract: | The neural network data fusion technology based system is designed to collect the motor vibration signals and current and voltage signals. The data is processed in real-time and partial diagnosed with neural network, then global analysis for the fault signals is conducted with data fusion techniques to determine the exact type of electrical fault. Through practical experience, the neural network data fusion technology, applied in fault diagnosis, has the advanteges of high identification probabili- ty, conveniences and high accuracy. |
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| Keywords: | neural network data fusion fault diagnosis fault signals |
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