基于 BP 神经网络的差压式浆液密度监测技术

摘要

Grout density monitoring has important significance for the control and effect evaluation of grouting process in the process of grouting .Traditional differential pressure density sensor is influenced by the pressure fluctuation of the grouting pump ,the dynamic additional force ,the change of the fluid velocity and the low flow velocity ,and it may have a large error which means it is only suitable for stationary liquid and relatively stableslurry .At the same time ,if the water cement ratio is small and glueyness is high ,the monitoring results are not accurate enough ,in order to ensure the effective evaluation of the grouting process and the effect of grouting ,it is urgent to develop monitoring equipment with high accu-racy and applicability .In this paper ,in allusion to the defects of differential pressure density sensor ,considering factors such as pressure ,pressure loss and flow velocity ,combined with the density calculation of BP algorithm ,a differential pressure slurry density monitoring sensor with high accuracy and stability has been developed which can be applied to all kinds of slurry and process of grouting engineering .%灌浆过程中浆液密度监测对于灌浆过程控制和效果评价具有重要的意义。传统的差压式密度传感器受到灌浆泵的压力波动、调压阀调节引起的动态附加力、浆液流速的变化和低流速时水泥浆液析水沉淀等因素的影响可能存在较大的误差，适用于静止液体和流速相对稳定的浆液；同时对于水灰比小、黏稠度大的浆液监测的准确性也较差。为保证对灌浆过程及灌浆效果的有效评价，亟需一种密度监测精度高、适用性强的比重监测设备。针对传统差压式密度传感器的缺陷进行优化，考虑压力、压力损失及流速等因素的影响，结合BP算法进行密度计算，研发了基于神经网络的差压式浆液密度监测设备，具有较高准确性和稳定性，可适用于各种浆液、工艺的灌浆工程。