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Research on Fire-Engine Pressure Balance Control System Based Upon Neural Networks

机译:基于神经网络的消防车压力平衡控制系统研究

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摘要

The pressure produced by the water coming out of the fire-engine pump outlet is controlled by the rotate speed of the fire pump. However, this RS is controlled through fire-engine accelerator voltage which is controlled by the ECU. In order to control and keep the fire-engine pressure balanced, it is necessary to take pressure, rotate speed and current rate as input parameters and control voltage as output parameter through BP neural network control system. Related researches indicate that BP neural network is appropriate for building the system whose target is to keep the pressure balanced. And, some modification can be done to the standard BP neural network algorithm. These modified BP neural network algorithms are BP neural network with momentum factors and self-adapting learning speed which can improve the response speed and performance of this control system dramatically.
机译:由消防泵出口流出的水所产生的压力由消防泵的转速控制。但是,此RS是通过由ECU控制的消防车加速器电压来控制的。为了控制和保持消防车压力平衡,必须通过BP神经网络控制系统将压力,转速和电流率作为输入参数,将控制电压作为输出参数。相关研究表明,BP神经网络适用于构建以保持压力平衡为目标的系统。并且,可以对标准BP神经网络算法进行一些修改。这些改进的BP神经网络算法是具有动量因子和自适应学习速度的BP神经网络,可以显着提高该控制系统的响应速度和性能。

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