石油含水率测量动态补偿模型研究

石油含水率测量动态补偿模型研究
Research on Measuring Moisture in Petroleum Based on Dynamic Compensation Metho

摘要:针对传统微波透射法测量石油含水率存在的测量误差大等问题，提出了一种基于神经网络的动态补偿方法，确定衰减和相移两个参量作为动态补偿模型的输人;针对传统BP算法具有收敛速度慢、容易陷人局部极小值等缺点，采用微粒群训练算法对神经网络动态补偿模型进行训练，可使微波透射石油含水率测量结果的补偿过程具有寻优全局性和精确性。实验结果表明，利用该技术对石油含水率测量结果进行校正是一种有效的方法，具有一定的应用价值。
关键词:石油含水率神经网络微粒群优化算法动态补偿测量精度

Abstract; To against the problem of big error in measuring moisture in petroleum by traditional microwave transmission method, the dynamic compensationte chniqueb asedo nn euralne tworkis p roposed.T woo fth ep arameters,i. e. m icrowavea tenuationa ndp hasesh ifta reta kenas thein putso fth ed ynamicc ompensationm odel.C onsideringth es hortcomingso fco nventionalB Pa lgorithm,e .g. c onvergings lowlya nde asily trapping a local minimum value, a learning algorithm using particle swarm optimization《PSO) is adopted to train the neural network。compensation model. This wil enable the compensation process optimal and accurate overal. Experiments show that the use of the technology in calibrating the measurement result of moisture in petroleum is efective and has certain applicable value.
Keywords;P etroleum Moisture Neuraln etwork Particle。optimizationa lgorithm Dynamicc ompensation Measurementa ccuracy