基于时空映射的加工过程数据监测与可视化分析

The data acquisition method of the machining processes was studied. The processing conditions were discretized in time domain and space, and the voxel model was introduced to subdivide and mark the part space and machining process signals. The short-time domain processing method was used to characterize the machining process signals as corresponding short-time domain signal characteristics. Thus, the knowledge association between the unit voxel working condition and the processing signals was established, and the time-position mapping model of the processing data and the part processing position was established. Finally, taking blade rough milling as an example, the spindle power was visualized and analyzed through the time-position mapping model based on processing signals. The power cloud map was generated, which clearly located the power out-of-tolerance area in blade machining, evaluated the machining state, and provided a basis for processing parameter optimization.