多个神经网络模型在磁力泵滑动轴承监测系统中的应用

The Application of Multiple Neural Network Model to the Monitoring System of Magnetic Drive Pump Sliding Bearing

为了用神经网络法来检测磁力泵滑动轴承的间隙,设计了滑动轴承的间隙检测系统的实验台,根据实验数据建立了神经网络模型;采用多个传感器同时采集位移电压和多个神经网络模型进行迭代求解的方法,实现了对滑动轴承间隙的检测。最后用实验验证了该检测系统的可行性。实验结果表明测量值与实际值很接近,所以用该方法建立的检测系统可行,并达到一定的精度。

In order to measure the clearance of magnetic drive pump sliding bearing by neural network, special experiment table was designed and neural network models were established on the basis of the data got by experiments. Multiple data-gathering sensors were used to gather displacement and voltage, multiple neural network models were used to get a result by iterative way, so that sliding bearing clearance can be measured. The feasibility of the monitoring system was validated by experiments. The results of experiments indicate that measured values are very close to the real values, thus the monitoring system established by the way could work and achieve some precision.