改进的旋转门算法及其在数控机床监控领域的应用

摘要

针对数控机床状态数据实时采集造成的占用大量存储单元,存储器过度消耗这一问题,为使海量的过程数据易于存储和回调,提出了一种基于旋转门(SDT)的改进算法对数据进行压缩.该方法能够根据数据的波动状态对容差进行动态调整;采用多模型寻优方法进行函数拟合;并根据拟合的误差保存对压缩精度影响较大的点.从而保证在尽量不丢失有效信息的情况下存储更少的机床状态数据,具有较好的压缩效果.%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. Besides, 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.