石油含水率測量動態補償模型研究
Research on Measuring Moisture in Petroleum Based on Dynamic Compensation Metho

摘要:針對傳統微波透射法測量石油含水率存在的測量誤差大等問題，提出了一種基于神經網絡的動態補償方法，確定衰減和相移兩個參量作為動態補償模型的輸人;針對傳統BP算法具有收斂速度慢、容易陷人局部極小值等缺點，采用微粒群訓練算法對神經網絡動態補償模型進行訓練，可使微波透射石油含水率測量結果的補償過程具有尋優全局性和精確性。實驗結果表明，利用該技術對石油含水率測量結果進行校正是一種有效的方法，具有一定的應用價值。
關鍵詞:石油含水率神經網絡微粒群優化算法動態補償測量精度

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