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为减小钝边刀盘负载、提高铣边机的生产节奏,分析铣边时的钢板进给速度、钝边刀盘的电动机负载与坡口刀盘速度设定值、铣屑厚度设定值、铣边量之间的函数关系,建立BP神经网络模型,以X70M1 067 mm×14.1 mm规格为例,结合实际数据,对构建的模型进行训练,将计算结果与实际值对比,证明模型可靠;将验证的模型泛化,找到坡口刀盘速度、铣屑厚度的较优设定值;经现场试验,铣边质量满足工艺要求,钢板进给速度、钝边刀盘电动机负载的计算值与实际值偏差较小。
In order to reduce the load of blunt-end cutter, increase the production rhythm of edge cutter, analyze the feed speed of steel plate during milling, the motor load of blunt cutter and bevel cutter, the setting value of milling cutter thickness , The amount of edge milling, the establishment of BP neural network model to X70M 1 067 mm × 14.1 mm specifications, for example, combined with the actual data, the model was trained, the calculation results and the actual value of comparison to prove that the model Reliable; to verify the model generalization, to find the bevel cutter speed, milling thickness of the optimal set value; the field test, milling quality to meet the technical requirements, steel feed speed, blunt cutter motor load calculation The deviation from the actual value is small.