基于神经网络技术的流量测量方法研究

Research on Flow Measurement Method Based on Neural Network

流体的流量直接反应设备的运行状况,在现代化的工业生产中,连续准确地监视流体的流量对于设备的安全、经济运行至关重要。鉴于流量测量的复杂性,将神经网络数据融合技术应用于流量测量,研究提高流量测量精度的方法。在此研究基础上,针对差压式流量测量的特点,设计出了基于神经网络数据融合技术的流量测量模型。

Flow represents the status of the equipments,it is essential to monitor it continually and accurately in modern industry. However,flow measurement is liable to suffer the influences of many complex factors,it is a difficult task.Thus,a method based on neural network data fusion is presented.Moreover,according to the characteristics of the pressure-difference flowrator,a flow measurement model based on neural network is designed,which applies the technology of multi-sensor information fusion to reduce the measurement error.The signals from several sensors are delivered to the fusion center to dispose.The fusion technology adopts the improving arithmetic of neural network.