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首页> 外文期刊>International Journal of Process Systems Engineering >Health condition diagnoses of power plants turbines aided by neural networks and vibration tools
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Health condition diagnoses of power plants turbines aided by neural networks and vibration tools

机译:神经网络和振动工具辅助的发电厂水轮机健康状况诊断

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摘要

In Brazil, a way of changing the aggressive exploitation of hydraulic potential resources, in order to produce electrical energy, was found by the new application of hydropower plants. A crucial characteristic is that a unique operator is responsible for several hydropower sites far away from each other. Faced with this geography problem, an intranet architecture has been developed and from this skilful application it is possible to use some intranet channels for transmission of a special data from a new technique of signal processing. Basically, this technique is a type of spectrum which uses fixed frequency bands and vibration severity levels. The special spectrum's data is issued to a neural network system which detects the fault in its early stages and a quickly and reliably automatically a diagnosis is obtained. The intranet system uses this diagnosis to transmit the real health condition of the machine in real-time, optimising both management maintenance and production.
机译:在巴西,水力发电厂的新应用发现了一种改变对水力潜在资源的积极开发以产生电能的方法。一个关键特征是,一个独特的运营商负责彼此远离的几个水力发电站。面对这一地理问题,已经开发了Intranet体系结构,并且从该熟练的应用程序中可以使用一些Intranet通道来传输来自信号处理新技术的特殊数据。基本上,这种技术是一种频谱,它使用固定的频段和振动严重性级别。特殊频谱的数据被发送到神经网络系统,该系统可以在早期阶段检测故障,并快速,可靠地自动进行诊断。 Intranet系统使用此诊断来实时传输机器的实际健康状况,从而优化管理维护和生产。

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