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基于神经网络数据融合技术的诊断系统的研究 被引量:5

Study on integrated fault diagnosis system based on neural network data fusion technology
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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。 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.
出处 《河北工业科技》 CAS 2010年第6期378-380,共3页 Hebei Journal of Industrial Science and Technology
关键词 神经网络 数据融合 故障诊断 故障信号 neural network data fusion fault diagnosis fault signals
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