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Application of Improved SDT Algorithm in CNC Machine Monitoring Field

机译:改进的SDT算法在数控机床监控领域的应用

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Considering to the problem of requiring and consuming a lot of storage units by collecting the real time data in the CNC machines, an improved Swinging Door Trending (SDT) compression algorithm has been proposed to compress the massive data. Its tolerance can be adjusted dynamically according to the trend of the fluctuations of the data. In addition, Multi-models optimization method was used for function fitting. And points which have great impact on the compression accuracy are saved according to the error of fitting. Less machine status date can be stored without losing valid information, and get a better compression results.
机译:考虑到通过在CNC机器中收集实时数据需要消耗大量存储单元的问题,提出了一种改进的SDT(Swinging Door Trending)压缩算法来压缩海量数据。可以根据数据波动趋势动态调整其容差。另外,使用多模型优化方法进行功能拟合。根据拟合误差保存对压缩精度有重大影响的点。可以存储更少的机器状态日期而不会丢失有效信息,并且可以获得更好的压缩结果。

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