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作 者:孙志勇 Sun Zhiyong(Xieguo Mine,Shanxi Xishan Jinxing Energy Co.,Ltd,Lyuliang Shanxi 033600,China)
机构地区:[1]山西西山晋兴能源有限责任公司斜沟矿,山西吕梁033600
出 处:《机械管理开发》2024年第10期85-87,共3页Mechanical Management and Development
摘 要:为了解决掘进机各关键部件在工况环境下发生振动破坏的问题,利用数值模拟软件对掘进机截割头进行工况分析,发现随着模态的不断增加,此时的固有频率呈现逐步增大的趋势,当模态为31时,掘进机最大变形值出现在支撑架位置,在此位置的变形最大值为1.782 2 mm。同时对掘进机在钻进和横截工况下的振动特性以及受力特性进行分析,随着时间的变化,此时的横截和钻进工况下,截割头合外力均呈现无规律变化情况,两种工况下的合力最大值分别为86 kN和50 kN,钻进工况对于截割头截齿的影响要强于横截工况,为后续截割头截齿设计提供一定的参考。In order to improve the error compensation effect of CNC machine tool turntable,a BP neural network optimization process is designed by genetic algorithm(GA),and the positioning error model of turntable is established by adding coordinate parameters and moving speed index.The GA optimization BP model was constructed by Matlab software,and after the optimization weights and thresholds were obtained,the results were transplanted into DSP to carry out modeling and prediction,which greatly improved the prediction rate.The results show that the machine tool turntable has different positioning errors at different spatial positions and rates,and the overall change characteristics are more complex.The model built by GA optimization BP neural network can achieve higher accuracy,and the error residual range is-0.5~0.5μm,which meets the actual demand.The research is helpful to improve the positioning accuracy of the machine tool turntable and enhance the machining accuracy.
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