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依据鹰厦线接触网检测车现有拉出值和列车振动检测数据及计算方法，提出了一种基于ＢＰ网络的新算法实现拉出值补偿计算，为供电段有效利用检测车动态检测数据指导静态检修提供了依据。实验结果表明：与人工测量值比较，误差＜３０ｍｍ的可达８０％。
Based on the existing pull-out value and train vibration detection data and calculation method of Yingxia Xiamen catenary inspection vehicle, a new algorithm based on BP neural network is proposed to realize the calculation of pullout value compensation and the guidance of dynamic detection data Static maintenance provided the basis. The experimental results show that compared with the manual measurement, the error of <30mm can reach 80%.